Development and experimental testing of an amphibious vehicle

Transcription

Development and experimental testing of an amphibious vehicle
DEVELOPMENT AND EXPERIMENTAL TESTING OF AN AMPHIBIOUS
VEHICLE
by
Joseph G. Marquardt
A Thesis Submitted to the Faculty of
The College of Engineering and Computer Science
in Partial Fulfillment of the Requirements for the Degree of
Master of Science
Florida Atlantic University
Boca Raton, Florida
May 2012
i
DEVELOPMENT AND EXPERIMENTAL TESTING OF AN AMPHIBIOUS
VEHICLE
by
Joseph G. Marquardt
This thesis was prepared under the direction of the candidate's thesis advisor, Dr. Karl
von Ellenrieder, Department of Ocean and Mechanical Engineering, and has been
approved by the members of his supervisory committee. It was submitted to the faculty
of the College of Engineering and Computer Science and was accepted in partial
fulfillment of the requirements for the degree of Master of Science.
arl von Ellenrieder, Ph.D.
Thesis AdVisor~_
Edgar An, Ph.D.
Palaniswamy Ananthakrisnan,
Ph.D.
..M-<.vvJ.A..~4A)~
a d Hashemi, Ph.D.
air, Department of Ocean and Mechanical
En ineering
Manhar Dhanak, Ph.D.
hammed Ily s Ph. .
Interim Dean, Co lege of Engineering and Computer
Science
~rZ~~
ii
ACKNOWLEDGEMENTS
I am so fortunate to have the most amazing family; Mom, Dad and Kasey, without
you guys in my life I would not have accomplished what I have, or be here about to turn
in a Master’s Thesis. Thank you for everything you have done for me, and your support
through the past few years of school. I am also extremely grateful for my girlfriend Lori
who has been there for me through everything, and always knows how to put a smile on
my face. Her motivation and inspiration keeps me determined and focused.
Dr. von Ellenrieder, my thesis advisor, thank you for everything you have done
and taught me along the way. You were always willing to help, even if I was the fourth or
fifth student in line waiting to talk to you. I also want to thank my thesis committee for
their help and support.
I would also like to thank Ed Henderson and Luis Padilla. I have learned so much
from the two of you in the past few years, and your willingness to help and teach is
unbelievable. Also, Dr. Ananthakrisnan, you are an amazing professor and I am so
fortunate to have taken classes with you. All my fellow graduate students, especially Tom
Furfaro, Janine Mask, Jose Alvarez, Matt Young and James Lovenbury, your help was
much appreciated.
Lastly, I would like to thank the Office of Naval Research for funding this
research.
iii
ABSTRACT
Author:
Joseph Marquardt
Title:
Development and Experimental Testing of an Autonomous
Amphibious Vehicle
Institution:
Florida Atlantic University
Thesis Advisor: Dr. Karl von Ellenrieder
Degree:
Master of Science
Year:
2012
The development and experimental testing of the DUKW-Ling amphibious
vehicle was performed during the first phase of an autonomous amphibious vehicle
system development project. The DUKW-Ling is a 1/7th scale model of a cargo transport
concept vehicle. The vehicle was tested in the three regions it is required to operate: land,
sea and the surf zone region. Vehicle characteristics such as turning radii, yaw rate and
velocities were found for different motor inputs on land and water. Also, because a
vehicle navigating the surf zone is a new area of research that lacks experimental data the
vehicle was tested in the breaking waves of the surf zone and its motion characteristics
were found, as well as the drivetrain forces required to perform this transition.
Maneuvering tests provided data that was used to estimate a model for future autonomous
control efforts for both land and water navigation.
iv
DEVEL
LOPMENT AND
A
EXPER
RIMENTAL
L TESTING OF AN AM
MPHIBIOUS
S
VEHICLE
E
LIST
L
OF FIG
GURES ............................................................................................................... vii LIST
L
OF TAB
BLES ................................................................................................................. xii NOMENCLA
N
ATURE ............................................................................................................. xiv 1 INTROD
DUCTION ........................................................................................................... 1 1.1 Prob
blem Statem
ment .................................................................................................... 3 1.2 DUK
KW 21 Back
kground............................................................................................. 6 1.3 Currrent Model Description
D
and History ................................................................. 8 1.4 Relaated Researcch ....................................................................................................... 9 1.4.1 DUKW Autonomy ........................................................................................... 9 1.4.2 Vehicle Beehavior ........................................................................................... 11 1.5 Con
ntribution ............................................................................................................ 14 2 APPROA
ACH .................................................................................................................. 21 2.1 Mod
dification, Upgrades
U
and
d System De sign ........................................................ 21 2.1.1 Mechanicaal Conversio
on ................................................................................ 21 2.1.2 Electrical, Sensor and Control Sysstem Design ........................................... 33 2.2 Exp
perimental Approach
A
.......................................................................................... 43 2.2.1 Sensor and
d Test Equip
pment Calibrration ...................................................... 44 2.2.2 Vehicle Teests .................................................................................................. 49 3 RESULT
TS ...................................................................................................................... 65 3.1 Veh
hicle Tests ........................................................................................................... 65 3.1.1 Rolling Reesistance Testing ........................................................................... 65 3.1.2 Locating Vehicle
V
Centter of Mass ................................................................. 67 3.1.3 Dynamom
meter Testing
g................................................................................... 70 3.1.4 Maximum
m Incline and
d Approach/D
Departure Anngles ................................... 75 3.1.5 Land Man
neuvering Ch
haracteristicss .............................................................. 83 3.1.6 Sea Maneu
uvering Chaaracteristics ................................................................ 107 3.2 Systtems Identifi
fication ........................................................................................... 121 3.3 Tran
nsition Regio
on Tests ........................................................................................ 130 3.3.1 Land-to-Sea .................................................................................................. 134 Sea-to-Lan
3.3.2 nd .................................................................................................. 138 3.3.3 Vehicle in
n the Surf-Zo
one ............................................................................. 142 3.4 Frou
ude-Krylov Excitation
E
Forces
F
........................................................................ 149 v
4 CONCU
ULUSIONS....................................................................................................... 152 4.1 Recommendatio
ons for Futurre Work..................................................................... 153 5 APPEND
DIX .................................................................................................................. 156 6 REFERE
ENCES ............................................................................................................ 219 vi
LIST OF FIGURES
Figure 1 – DUKW 21 Concept ........................................................................................... 1 Figure 2 - DUKW SWATH Hull ........................................................................................ 7 Figure 3 – Original 1/7th Scale DUKW-ling ....................................................................... 9 Figure 4 - Original Vehicle with Wheel Drivetrain .......................................................... 22 Figure 5 – Original Five Wheel Drivetrain ....................................................................... 24 Figure 6 - New Chain vs. Original .................................................................................... 25 Figure 7 - Tracked Vehicle Separation Ratios .................................................................. 26 Figure 8 – Tracked Drivetrain........................................................................................... 26 Figure 9 - Conveyor Belt Track ........................................................................................ 27 Figure 10 - FBD of Vehicle Rolling Resistance ............................................................... 29 Figure 11 - Gearing System Numbering Convention ....................................................... 30 Figure 12 - Gear System Torques ..................................................................................... 32 Figure 13 - Water Sensor Schematic ................................................................................ 36 Figure 14 – RoboteQ’s RoboServer Software Operation ................................................. 38 Figure 15 - Motor Controller Hexadecimal Communication ........................................... 38 Figure 16 – Container Lifting Mechanism........................................................................ 39 Figure 17 –Control System Block Diagram...................................................................... 40 Figure 18 - PCB Motherboard .......................................................................................... 43 Figure 19 - Xsens Magnetic Field Mapper ....................................................................... 47 Figure 20 - Dynamometer Calibration .............................................................................. 49 Figure 21 - Rolling Resistance Tests ................................................................................ 51 vii
Figure 22 - Vehicle During Land Testing ......................................................................... 53 Figure 23 - ABS Turning Circle Test [39] ........................................................................ 54 Figure 24 – Autonomous Control ..................................................................................... 58 Figure 25 - ABS Figure Zig-zag Maneuvering Test [39] ................................................. 60 Figure 26 - Center of Mass Pendulum Test ...................................................................... 67 Figure 27 - Roll Response in Pendulum Test ................................................................... 69 Figure 28 – Dynamometer Test Results: Current-Torque Relationship at
Different RPMs ..................................................................................................... 71 Figure 29 - Dynamometer Test Results: RPM-Torque Relationship................................ 73 Figure 30 - Dynamometer Test Results: Current Torque Relationship for
Different Motor Commands .................................................................................. 74 Figure 31 - Vehicle Approach and Departure Angles ...................................................... 76 Figure 32 - Motor Data 11 Degree Incline Test ................................................................ 78 Figure 33 - Pitch Angle 11 Degree Incline Test ............................................................... 78 Figure 34 - Motor Data 14 Degree Incline Test ................................................................ 80 Figure 35 - Pitch Angle 14 Degree Incline Test ............................................................... 80 Figure 36 – Motor Data 19 Degree Incline Test ............................................................... 82 Figure 37 - Pitch Angle 19 Degree Incline ....................................................................... 82 Figure 38 - Minimum Turning Radius on Land................................................................ 84 Figure 39 - Clipped Data to Calculate Minimum Turning Radius ................................... 85 Figure 40 - Maximum Velocity on Land .......................................................................... 88 Figure 41 - Maximum Velocity Motor Current ................................................................ 88 Figure 42 - Maximum Velocity Motor Commands .......................................................... 89 Figure 43 - Rate of Turn During Maximum Speed (Test 1) ............................................. 90
viii
Figure 44 - Rate of Turn During Maximum Speed (Test 2) ............................................. 91 Figure 45 - Rate of Turn During Maximum Speed (Test 3) ............................................. 91 Figure 46 - Rate of Turn During Maximum Speed (Test 4) ............................................. 92 Figure 47 - IMU Yaw Rate for Equal Motor Commands ................................................. 93 Figure 48 - Maximum Speed Compass Heading (Test 1)................................................. 94 Figure 49 - Maximum Speed Compass Heading (Test 2)................................................. 94 Figure 50 - Maximum Speed Compass Heading (Test 3)................................................. 95 Figure 51 - Maximum Speed Compass Heading (Test 4)................................................. 95 Figure 52 - Straight Line Track with Correction Factor ................................................... 97 Figure 53 - Yaw Rate During a Turn to Port .................................................................. 100 Figure 54 - 105/75 Left Turn Current and Force on Tracks ........................................... 102 Figure 55 - 105/45 Left Turn Current and Force on Tracks ........................................... 102 Figure 56 - Vehicle Heading During a Land Right Turn ................................................ 104 Figure 57 - Continuous Compass Data During Land Right Turn ................................... 105 Figure 58 - 70/40 Land Zig-zag Test .............................................................................. 106 Figure 59 - Final Vehicle in Water Test Area................................................................. 107 Figure 60 - Minimum Turing Radius in Water ............................................................... 108 Figure 61 - Maximum Velocity Water............................................................................ 109 Figure 62 - Motor Current During Maximum Velocity Test Water ............................... 110 Figure 63 - Motor Commands During Maximum Velocity Test Water ......................... 110 Figure 64 - Straight Line Track in Water........................................................................ 112 Figure 65 - Compass Heading During Straight Track .................................................... 112 Figure 66 - IMU Yaw Rate Full Speed Water ................................................................ 113
ix
Figure 67 - GPS Yaw Rate Full Speed Water................................................................. 113 Figure 68 – Yaw Rate During a Turn to Port (100 Stbd, -80 Port) ................................ 119 Figure 69 - 122/0 Water Zig-Zag Motor Commands...................................................... 120 Figure 70 - Vehicle Position in Water Zig-zag Test ....................................................... 121 Figure 71- Motor Commands Land Zig-zag for Systems ID .......................................... 123 Figure 72 - Body Fixed u Velocity Model-Black Signal is the Measured Velocity ....... 123 Figure 73 - Body Fixed v Velocity Model-Black Signal is the Measured Velocity ....... 124 Figure 74 - Yaw Rate Model-Black Signal is the Measured Yaw Rate ......................... 124 Figure 75 - Body u Velocity Model on Second Data-Black Signal is Measured
Velocity ............................................................................................................... 125 Figure 76 - Body v Velocity Model on Second Data-Black Signal is Measured
Velocity ............................................................................................................... 125 Figure 77 - Yaw Rate Model on Second Data-Black Signal is Measured Yaw Rate ..... 126 Figure 78 - Body Fixed v Velocity Land Model-Black Signal is Measured Velocity ... 128 Figure 79 - Body Fixed v Velocity Model Land-Black Signal is Measured Velocity ... 128 Figure 80 - Yaw Rate Model Land-Black Signal is Measured Yaw Rate ...................... 129 Figure 81 - Dania Beach Ocean on Test Day ................................................................. 131 Figure 82 - Wave Gauge Output ..................................................................................... 132 Figure 83 - Wave Data in Surf Zone Tests ..................................................................... 133 Figure 84 - Land-to-Sea Transition Motor Data (Motor Command: 80)........................ 135 Figure 85 - Land-to-Sea Transition Motions (Motor Command: 80) ............................. 135 Figure 86 - Beach-to-Sea Vehicle Track ........................................................................ 136 Figure 87 – Sea-to-Land Vehicle Track.......................................................................... 139 Figure 88 – Sea-to-Land Transition Motor Data (Motor Command: 80) ....................... 140
x
Figure 89 - Sea-to-Land Transition Motions (Motor Command: 80) ............................. 140 Figure 90 - Motions in the Surf Zone Test 1 .................................................................. 142 Figure 91 - Motions in the Surf Zone Test 2 .................................................................. 143 Figure 92 - Motions in the Surf Zone Test 3 .................................................................. 143 Figure 93 - Motions in the Surf Zone Test 4 .................................................................. 144 Figure 94 - Motions in the Surf Zone Test 5 .................................................................. 144 Figure 95 - Waves in a 20 Second Period ....................................................................... 147 Figure 96 - Wave Frequency in Surf-zone ...................................................................... 148 Figure 97 - Roll, Pitch and Heave Frequency Response to Surfzone ............................. 148 Figure 98 - Surge (1), Sway (2), Heave (3) Force vs. Time ........................................... 149 Figure 99 - Roll (4), Pitch (5), Yaw (6) Moments vs. Time ........................................... 150 xi
LIST OF TABLES
Table 1 - DUKW Characteristics ........................................................................................ 8 Table 2 – Gearing Equations............................................................................................. 31 Table 3 - Gearing Spreadsheet .......................................................................................... 32 Table 4 - Land Motor Inputs for Motor Command Circle Tests ...................................... 55 Table 5 - Water Motor Inputs for Motor Command Circle Tests ..................................... 57 Table 6 - Rolling Resistance Test Results ........................................................................ 66 Table 7 - Average Current and Track Force in 11 Degree Incline Test ........................... 79 Table 8 - Average Current and Track Force in 14 Degree Incline Test ........................... 81 Table 9 – Average Current and Track Force in 19 Degree Incline Test ........................... 83 Table 10 – Coordinates for Minimum Right Turning Radius Calculations...................... 86 Table 11 - Coordinates for Minimum Left Turning Radius Calculations ........................ 86 Table 12 - Maximum Velocity and Accelerations on Land .............................................. 87 Table 13 – Land Left Turn Radii ...................................................................................... 98 Table 14 – Land Right Turn Radii .................................................................................... 99 Table 15 - Land Left Turn Yaw Rate.............................................................................. 101 Table 16 - Land Right Turn Yaw Rate ........................................................................... 101 Table 17 - Land Zig-zag Test Motor Commands ........................................................... 106 Table 18 – Coordinates for Minimum In-Water Turning Radius Calculations .............. 108 Table 19 - Maximum Velocity and Acceleration in Water............................................. 109 Table 20 - Wind Data During Straight Line/Max Speed Tests ....................................... 111 Table 21 – Wind Data During Left Turn Tests ............................................................... 115 xii
Table 22 - Wind Data During Right Turn Test ............................................................... 115 Table 23 - Water Left Turning Radii .............................................................................. 116 Table 24 - Water Right Turing Radii .............................................................................. 116 Table 25- Water Left Turn Yaw Rate ............................................................................. 117 Table 26 - Water Right Turn Yaw Rate .......................................................................... 118 Table 27 - Land-to-Sea Drivetrain Force Results ........................................................... 138 Table 28 – Sea to Land Drivetrain Force Results ........................................................... 141 Table 29 - Average Motions Test 1 ................................................................................ 145 Table 30 - Average Motions Test 2 ................................................................................ 145 Table 31 - Average Motions Test 3 ................................................................................ 145 Table 32 - Average Motions Test 4 ................................................................................ 145 Table 33 - Average Motions Test 5 ................................................................................ 146 Table 34 - Average of all Surf Zone Motion Test Results .............................................. 146 xiii
NOMENCLATURE
Autonomous: Capable of performing a task without human interaction
SWATH: Small Water plane Area Twin Hull
Stereo Vision: Dual camera system that allows depth perception by triangulation
Amphibious: Capable of traveling in both aquatic and terrestrial environments
IMU: Inertial Measurement Unit
DGPS: Differential Global Positioning System, uses ground based stations as well as
satellites and has two GPS receivers to compare location data
HSV: Hue, Saturation and Value. A cylindrical coordinate representation of color
RGB: Red, Green and Blue. An additive representation of color
AWP: Water plane area of a hull form
DUKW: GMC terminology: “D” vehicle designed in 1942, “U” utility, “K” all-wheel
drive, “W” two powered rear axles.
SBC: Single Board Computer. This projects used an ARM9 based TS-7800 by
Technologic Systems.
xiv
1
INTRODU
UCTION
The DU
UKW 21 is a SWATH vehicle
v
that will be usedd to supply offshore shiips in
areas wheree convention
nal methodss of supply may be diffficult or im
mpractical. D
Deepwater portss and desig
gnated infraastructure w
will no lonnger be reqquirements w
when
supplying ships
s
from shore.
s
Redu
ucing onsho re footprintt and logistiics are the main
benefits of amphibious
a
cargo transp
port, becausee it reduces the cost andd complexityy of a
supply misssion by com
mbining the task of twoo or more vvehicles. Maaking the veehicle
autonomouss would alsso simplify
y the cargoo transport mission, alllowing muultiple
unmanned DUKW
D
21’ss to be supervised by a single persoon. This conncept, picturred in
figure one below, is a unique app
plication of an autonom
mous vehiclee because itt will
ween land and sea, and
a
providdes an oppportunity too study a new,
travel betw
unconventio
onal applicattion of auton
nomous systeems.
Figurre 1 – DUKW 21 Concept
1
An autonomous amphibious vehicle, however, does not entirely relate to typical
autonomous projects, and provides engineers with a new design challenge. Autonomous
vehicles have historically been designed for use in a specific operating environment.
The DUKW 21 will be one of the first autonomous vehicles that will travel on both land
and sea. The transition between the two is in the highly dynamic and energetic surf
zone, which is the most complex area of research for this autonomous system, due to a
lack of experimental research. The vehicle’s dynamic response is a very important
factor in the design of a control system, and its maneuvering characteristics must be
well defined in each regime that the vehicle must operate. The lack of experimental data
for a vehicle transitioning between land and sea makes it difficult to design an
autonomous model for control. Experimental data is especially important in an area
such as the surf zone, where modeling is difficult due to the non-linear nature of
breaking waves. The dynamic motions of the vehicle must be defined in experimental
testing, and the performance of the autonomous control system must also be determined
in experimental tests.
Autonomous vehicles have historically been used in a single operating
environment [32]. Whether a vehicle primarily operates in the air, on land, underwater
or on the surface will dictate the type of sensors and control method used to control the
vehicle autonomously. Autonomous vehicles use sensors and control algorithms unique
to the area in which they must perform their mission. An amphibious vehicle must
operate well in both terrestrial and aquatic environments; thus, posing a design
challenge for engineers. A system designed for land navigation and control is much
different than that of a sea-going surface vehicle, in both the sensors used and control
2
techniques. A unique system thatt can perfoorm well accross the veehicle’s diffferent
operating en
nvironments is a significcant challengge for this cooncept.
The focus
fo
of this thesis work
k was to dessign, build aand test a mechanical, sensor
and electriccal system that
t
improveed the capabbilities of thhe DUKW-lling model. This
work was completed
c
to
o improve the
t ability ffor testing aand autonom
mous amphibbious
system deveelopment. Ex
xtensive testting of the uupgraded veehicle was peerformed annd the
data are disccussed. The final producct of this thessis is a baselline vehicle that is robusst and
easy to use,, and an exp
perimental an
nalysis of thhe open loopp performance characterristics
of the vehicle in the diffferent areas it
i operates.
This document
d
in
ntroduces th
he backgroun
und and devvelopment off the DUKW
W 21
concept, preesents relevaant research in the area of vehicle ttesting, specifically surff zone
testing, then
n describes the modificcation and eexperimentall approach tthat was used to
fulfill the goals
g
of this thesis. A deetailed resullts section, a discussionn of these reesults,
recommend
dations for fu
uture work, and a projeect timeline outlining thhe progressioon of
this thesis work,
w
are also
o included.
1.1
Probllem Statem
ment
In ord
der to perform
m its missio
on, there are two main taasks the full scale DUKW
W 21
will need to
o complete. First,
F
it must be able to navigate to its intendedd location ussing a
control algo
orithm that performs
p
weell across thhe different environmennts the vehiccle is
required to operate.
o
Its sensor
s
system
m will be a uunique combbination of ssensors not ffound
on current autonomous
a
vehicles, wh
hich primarilly do not opeerate across different
3
operating environments. Secondly, it must be able to avoid obstacles while performing
its navigation task, and the performance of techniques used on surface vehicles and land
vehicles is unknown in the dynamic surf zone region, where the vehicle will experience
random, fast accelerations when encountering breaking waves.
Autonomous control on land and at sea utilizes common techniques and methods
of control. The transition zone, defined as the area between terrestrial and aquatic
operating environments, is the main area of uncertainty in the development of this
autonomous system. This energetic and dynamic surf zone contains breaking waves,
which are highly random and difficult to predict. The motions and accelerations the
vehicle will experience are important for the development of the vehicle’s structure as
well as its autonomous control system. Because breaking waves are highly non-linear,
they are difficult to simulate, making experimental testing the ideal technique to
understand how a vehicle responds in this area. The lack of experimental data is an
obstacle in the development of this concept and must be expanded. This information can
be obtained using a model vehicle and collecting data with the onboard sensors. The
forces the vehicle experiences, as well as the drivetrain forces required to navigate the
vehicle through the surf zone are explored with experimental testing.
Previous algorithm development for the DUKW at the Center for Innovation in
Ship Design (CISD) was limited because of the lack of experimental data available for a
vehicle transitioning between land and sea through the surf zone. The drivetrain forces
in the transition region, maximum drivable gradient, the vehicle’s turning radius and
driving characteristics, as well as the vehicle’s dynamics in different sea states are
4
unknown because this is a new area of research, and there is a lack of applicable
experimental data and research [8].
The forces required to complete a transition between land and sea are unknown,
and are important for full scale design, particularly for the power plant design.
Modeling and algorithm development work in recent years also has identified this as a
setback.
Models for autonomous control are based on the operating conditions of the
vehicle. How it reacts to input functions, such as turning a wheel or rudder, must be
understood in the development of the control system. A vehicle’s response to a change
in heading is very different on land compared to sea, and this response will also differ in
the surf zone. Therefore, it is assumed diverse methods of control must be used
depending on the environment the vehicle is in. The vehicle’s response to motor
commands is important in autonomous control development and must be found through
experiments with the vehicle model.
For obstacle avoidance, the vehicle must have a sensor or combination of sensors
that provide information to the control system about the vehicles surroundings. The best
system to use for a vehicle operating in the surf zone is unknown at this time and
different approaches must be tested experimentally to determine the most effective
sensor choice. Stereo vision is a possible solution to this aspect of design, because it has
performed well on autonomous surface vehicles in the past [30]. JPL developed an
autonomous vehicle called the CARACaS, Control Architecture for Robotic Agent
Command and Sensing, which used stereo vision to navigate through bridge pilings.
5
The perform
mance of vission-based navigation
n
onn a vehicle eexperiencingg breaking w
waves
in the surf zone is unk
known at th
his time. A further undeerstanding oof the limitaations
w the acceelerations an
nd responses of the vehiccle in this reegion is needded to
associated with
determine th
he feasibilitty of vision--based naviggation in thhe surf zone. A vision bbased
obstacle reccognition sysstem must be
b developedd for experim
mental testinng on the veehicle
model.
1.2
DUKW
W 21 Backg
ground
The current metho
od of supply
ying a fleet iis by the usee of large traansport ships like
peed-RO-RO
O (LMSR) ships that require ddeep-water pports.
the Large Medium-Sp
Locating, developing
d
and
a securing
g such a poort poses a challenge, yyet supplyinng an
offshore fleeet is an essen
ntial elemen
nt of any misssion. Currennt solutions tto the supplyy line
involve the use of heliicopter transsport for sm
mall amountss of cargo, oor teams off land
vehicles and
d landing crraft. These methods
m
are inefficient in both costt and compllexity
[13].
The armed forrces have continuouslyy recognizeed amphibious vehiclees as
l
tools because they
t
do not require a doock or have draft limitattions.
significant logistics
The ability to come ashore
a
witho
out a port or designatted infrastruucture makees an
amphibious vehicle a beeneficial cho
oice for a suppply missionn.
In orrder to addreess the need for a supplyy line from sshore to the fleet, the DU
UKW
21 has been
n under deveelopment at The
T Center for Innovatiion in Ship D
Design (CIS
SD) at
the Naval Surface Warfare
W
Cen
nter/Carderocck Divisionn (NSWC/C
CD) since 2007
[13][25]. Th
he DUKW 21
2 concept provides
p
shipp replenishm
ment from shhore by meaans of
6
container deelivery, even
n in areas weere a port m
may not be reeadily availaable. The DU
UKW
21 is a Sm
mall-Water-Pllane-Area, Twin
T
Hull ((SWATH) vvehicle with a superstruucture
designed to lift and tran
nsport a 20-ffoot ISO conntainer. Thee arching struucture proviides a
simple yet strong
s
design
n for operatio
on in the eneergetic surf zzone [13].
A SW
WATH hull was used in
n this design because of its stability ccharacteristiics. A
SWATH hu
ull has a larrge amount of its displaacement locaated below the waterlinne, as
seen in figu
ure 2 below
w. Because of
o this, the hull’s wateer plane areaa is significcantly
reduced, inccreasing its stability chaaracteristics. The hull coonfigurationn is promisinng for
transporting
g cargo throu
ugh an area with potentiially hazardoous conditioons. The DU
UKWling water-p
plane area is 1380 [in2].
Figuree 2 - DUKW S
SWATH Hull
The originall requiremen
nts for the fu
ull scale DUK
KW 21 are aas follows [113]:









Operrate in up to Sea State 2 (SS2)
Delivery of carg
go from 5 nm
m offshore too 5 nm inlandd
Cruiise at 15 kno
ots in water and
a 30 km/hhour on land
Clim
mb a standard
d beach grad
dient (1:50)
Load
d/unload ISO
O container automaticall
a
ly
Be controlled
c
by
y either a sin
ngle crew meember or by automatic, uunmanned
conttrol
Deliver 10 ISO containers
c
without
w
refueeling
Enteer the well deeck of an LP
PD
Lift a loaded 20 foot ISO container weigghing 24,0000 kg (53,0000 lbs)
7
1.3
Curren
nt Model Deescription an
nd History
The DUKW-ling
D
g, a 1/7th sccale model, was develloped by M
Maritime Appplied
Physics Corrp. (MAPC)) for the CISD to demoonstrate andd study the feasibility oof the
DUKW 21 in
i an amphib
bious cargo transport
t
miission [25].
As part
p
of the 2010 Floriida Atlanticc Universityy Ocean Engineering S
Senior
Design projject, the DU
UKW-ling model
m
was ggiven to a sstudent team
m where a sensor
network, co
ontrol system
m and lifting
g mechanism
m were desiggned and im
mplemented. This
initial senso
or network allowed
a
for basic autonnomous naviigation and included a GPS,
compass, RF
R transceiveer, proximity
y sensors, ddepth sensorr and a cam
mera. The veehicle
uses a forkllift style carrgo-handling
g mechanism
m, which alllows it to raaise and seccure a
scaled ISO container. The
T DUKW-ling model w
with its initiial sensor coonfiguration prior
own in figurre three, and its principlee characterisstics in table 1.
to this thesiss work is sho
Table 1 - DUKW Ch
haracteristics
LOA
106”
LWL
100”
Draft
19.3”
BOA
45”
BWL
35”
AWP
1380 in
32”
H Separation
Hull
2
L/B
2.36
TPI
0.022
PPI
50
D
Displacement
648 lbs
8
Figure 3 – Original
O
1/7th S
Scale DUKW--ling
1.4
Relateed Research
An au
utonomous, amphibiou
us vehicle iis a new cconcept thatt has very little
background
d informatio
on in the form
f
of expperimental data or com
mmon pracctices.
However, th
here is relev
vant research
h that can bee used to deevelop a wayy of studyinng the
concept thaat can be taailored to ap
pply to an amphibious vehicle. U
Understandingg the
vehicle’s beehavior is im
mportant in the developpment of a system thatt will controol the
vehicle auto
onomously. The
T followin
ng sections w
will discuss ccurrent reseaarch as it perrtains
to this projeect.
1.4.1
DUK
KW Autonom
my
Auto
onomous sy
ystems typiccally consisst of four ccomponents,, which incclude:
perception interface
i
(sen
nsors), a plaanner (path pplanning), ann executive ((sends comm
mands
to actuators)) and an actu
uator interfacce [8]. It cann be understoood an autonnomous vehiicle
9
on land would have a very different autonomous system than one on water. While the
required sensors would be an obvious difference between the two, the path planning
component of the autonomous system is also a very significant difference. Land
vehicles typically use batch path planning, which define a complete path from present
location to final destination [26]. This method is used because ground terrain is mostly
static, and does not change suddenly. So if a path needs to be altered, it usually does not
need to be recalculated from scratch because most of the path would be unaffected [11].
Autonomous sea surface vehicles typically do not use batch planning algorithms
because the dynamic nature of the ocean environment means extensive computations.
These vehicles use continuous path planning, defining a point short of the final
destination and is modified as the vehicle travels closer to its destination. This method
only plans for short term and does not take the entire environment into account [8]. A
unique system for controlling an amphibious vehicle must be developed to perform an
autonomous mission across different environments.
The CISD, and intern Benjamin Flom, have been developing control algorithms
specific to the DUKW 21 project. In his research, control techniques for each region are
proposed, and recently, his main focus has been the transition region [8][13]. The
research has certain setbacks due to lack of experimental data in the area. In order to
further the development of control algorithms, there are many unknowns that must be
explored. The first is the effective weight of the vehicle as it comes into contact with
shore. Common ground navigation algorithms assume a constant weight, which would
not be applicable here. His research takes into account the effective weight of the
10
vehicle as a function of
o the buoyaant force andd the beach incline. In order to usee this
approach, it is necessaary to 1) determine thhe slope thee vehicle enncounters annd 2)
g
th
he displacedd volume off the vehiclee as it com
mes in
determine a function governing
contact with
h land to obttain the effective weightt of the vehiicle [13]. In addition to these
hydrostatic data, also important
i
arre the dynaamic forces of the wavves acting onn the
vehicle and the resulting
g vehicle mo
otions they ccause. The rresearch alsoo suggests, thhat in
order to better develop the control algorithms,
a
tthe vehicle’s constraintss, such as tuurning
radius and maximum
m
drivable
d
grad
dient should be determinned, as welll as the vehicle’s
dynamics in
n different seea states [8].
1.4.2
Vehiicle Behavio
or
There are many common
c
praactices and ttests that aree performedd to understaand a
vehicle’s dy
ynamic charaacteristics [3
34][39]. The se tests define the dynam
mic behavioor and
motions of a vehicle wh
hile navigating. Many off these tests are perform
med in a test basin
or in the opeen ocean and
d do not partticularly appply to this prroject, since testing will be in
the surf zon
ne. This testiing will be in
i a beach eenvironmentt, where the use of a rottating
arm or plaanar motion mechanism
m (PMM) iis not possiible. These methods ddefine
maneuverin
ng coefficien
nts by subjeecting a mo del to speciific maneuvvers. Exploring a
model’s resp
ponse to breeaking wavees and definiing coefficieents in the suurf zone is a new
problem and
d will requirre a new apprroach on tessting techniqques.
In a teest basin, LE
EDs can be placed
p
on thee vehicle annd the use off fixed camerras at
known positions can deetermine thee models mootion when eencounteringg waves. In these
types of tessts, waves can be described as a fuunction of tiime and possition. Usingg this
111
information, the measured response of the model can be related to the wave it
encounters by the time and position in the basin. This method is described in [16],
where motions of the model were matched to time histories of the waves to determine
the vehicle’s response to certain waves. This method requires a test basin and controlled
wave making that cannot be directly applied in this project.
The Naval Surface Warfare Center/Carderock Division conducted model testing
of a 514 foot heavy lift ship experiencing breaking waves in their wave tank during the
summer of 2008 [28]. In this experiment, a beach was created to produce both spilling
and plunging waves. The model was then positioned at different locations in the
breaking waves where heave and pitch motions, and surge forces, were measured. A
heave post was attached to the longitudinal center of gravity and used a block gauge and
a dashpot to measure the force and pitch angle. An ultrasonic distance sensor was used
to measure the heave motions. Wave probes were positioned at different locations in the
wave tank to measure the waves as they progressed, to relate the motions measured to
waves encountered, and determine RAO transfer functions [28][29]. Understanding
these motions will be important in the development of this concept. Predicting how the
full scale vehicle reacts to breaking waves will be a key design parameter with regards
to both control and mechanical systems. This experiment is a good example of altering
known techniques to apply to a new problem; a ship encountering breaking waves in the
surf zone.
The information gathered by this experiment was passed to The University of
Hawaii, and analyzed by Miguel Quintero for his master’s thesis. From the data
12
gathered during model tests, the spectra were calculated and the dominant harmonics
were used to develop transfer functions that related the model response to the location
the wave broke on the hull. The project found for plunging waves, very strong second
order responses were seen, while spilling waves had dominant first order responses
[29].
Another issue that amphibious vehicles will face is the structural load experienced
while traveling through breaking waves. The most significant structural force comes
from slamming motions when a model was tested in regular, non-breaking waves. The
slamming motions a vehicle will experience in breaking, surf zone waves is assumed
much greater than in non-breaking waves, but must be further explored to understand
the slamming that can be expected in this area, and consequently, the structural forces
that will be experienced in such a region [29]. These slamming motions will increase
the force exerted on the drive system when the vehicle travels in shallow water, and
comes in contact with the sea floor. The SWATH hull reduces these slamming forces,
however wave slapping forces will be significant because it will be traveling through
the breaking waves of the surf zone.
In the experiments of [15], a model was towed through different non-breaking
wave patterns to understand the heave and pitch motions that the model would exhibit.
They found linear responses for long wavelengths, but as wavelengths became shorter,
the response became non-linear and was dominated by second order harmonics [15]. As
a wave approaches shore in the transition region, its wavelength becomes shorter, which
means the response can be assumed highly non-linear and therefore difficult to predict.
13
At these sho
ort waveleng
gths, breakin
ng waves willl produce a response whhere second order
harmonics will
w be a cau
use for conccern. The foorces acting on the vehiccle in this reegion
are unknow
wn at this tim
me due to laack of experrimental reseearch, but arre assumed to be
very significcant [29].
Comm
mon techniqu
ues to underrstand the dyynamic behaavior of a vehicle can bee seen
in [34] and
d [28]. Thesse open loop
p tests definne maneuveering characcteristics thaat are
unique to an
ny vehicle. The understtanding of thhis dynamicc behavior is essential iin the
developmen
nt of an autonomous con
ntrol system. The tests arre simple proocedures thaat can
be carried out
o with bassic sensors and determiine valuablee informatioon about vehhicles
maneuverin
ng characteriistics and deetermine conntroller gainns. Sea trial informationn can
also be used
d with a Kallman filter and
a regressioon to estimaate maneuveering coefficients,
motion variables and hy
ydrodynamicc forces. Thhis method, ccalled the “eestimation bbefore
modeling teechnique,” was
w tested usiing sea trial data of a tannker in [39].
Slidin
ng mode con
ntrol could prove
p
to bee very usefuul in the auttonomous coontrol
system on th
he DUKW 21.
2 This metthod changees the dynam
mics of a nonnlinear systeem so
it is not a fu
unction of tiime. It was used
u
in [8] ffor the contrrol of a wheeeled robot iin the
presence off skidding effects
e
and experimenta
e
al results vaalidate its efffectiveness.. The
dynamic natture presenteed in this con
ncept of a trracked vehiccle transitionning betweenn land
and sea mak
ke sliding mo
ode control a possible m
method for coontrol.
1.5
Contribution
The goals of this thesis
t
are to experimentaally characteerize the opeen loop, dynaamic
114
performance characteristics of the DUKW-Ling; to perform systems identification of
the vehicle on land, water and the surf zone; and to refine the design of the vehicle to
facilitate autonomous control system development. The transitional surf zone is the
main area of interest during development of the vehicle, for this thesis work as well as
in planned future research. The project is broken into two stages, the first being vehicle
design, modification and upgraded system development; and the second stage is
experimental testing and data analysis. The vehicle’s original drivetrain, sensors and
electronics were not adequate for planned testing and autonomous control system
development. The drivetrain was converted to a tank track system, because the vehicle
difficult to operate in sand, where much of the planned research will take place. This
conversion also produced a vehicle model more similar to the full scale design concept,
so experimental testing is more applicable. A unique amphibious vehicle sensor suite,
motherboard PCB and electrical system were designed and implemented on the
DUKW-ling model. The new system has sensors that are now adequate for extensive
vehicle testing and future autonomous control development. This sensor suite was tested
individually, as well as integrated on the vehicle as a complete system operating on
land, at sea and in the surf zone test areas to verify its performance.
A vision-based obstacle detection system was also developed and tested. With
further refinement, it may be possible to use this system for object detection and
localization. Preliminary testing of the system shows it is capable of locating and
tracking objects, and the system can be integrated into a future autonomous control
system for obstacle avoidance and vision based navigation. The system uses OpenCV
15
open source software to perform computer vision tasks. A detailed description of the
vision system work is given in Appendix 3.
The second focus of this thesis was experimental testing of the vehicle’s
characteristics. These tests will be further explained in this report, and include:
maneuvering tests, identification of vehicle forces in the transition zone, vehicle
motions in the surf zone, measurement of the vehicle’s response to motor input
commands, and determination of basic vehicle characteristics such as turning radius,
velocity and acceleration on land and at sea.
One of the most significant difficulties facing modeling research and algorithm
development for amphibious vehicles is the lack of experimental data [8]. More
specifically, CISD reports mention a lack of drivetrain forces in the transition region,
maximum drivable gradient, the vehicle’s turning radius and driving characteristics, as
well as the vehicle’s dynamics in different sea states as impediments to algorithm
development for amphibious vehicles [8]. These issues were addressed, and
experimental data is now available to Flom and others to develop these algorithms. This
data will also be useful for future projects that explore a multi-terrain vehicle which
transitions between land and sea, like the DUKW 21.
Because FAU contributes to the development of many autonomous vehicles, a
universal control system that is modular and can be used on more than one vehicle
could be useful to ease autonomous system development. By creating a universal
electrical and sensor system network, future projects would only need to make minor
16
modifications and add their unique requirements to a baseline system. They could also
build on existing software development of previous projects, simplifying the
development of the autonomous vehicle, since many of the projects over the past five
years at FAU have been similar. In the design of the sensor and electronics system of
this project, the ability for it to be used on similar vehicles was taken into consideration
when appropriate, in hopes that this system could be built upon after this project is
complete. The motherboard PCB was designed to facilitate the requirements of this
project, while also adding additional features that could be of use to similar projects in
the future by using the flexibility of the deigned system.
The detailed contributions of this project are shown below.
1. Systems Upgrade

Vehicle was upgraded to allow for adequate testing and control as an
autonomous amphibious vehicle. This includes upgraded electrical and
sensor systems, as well as a new tank track drivetrain to replace the wheeled
drivetrain originally on the vehicle. This will be outlined in detail in section
2.1.

Upgraded sensors such as a GPS enabled IMU and a differential GPS have
been integrated onto the vehicle to improve test data and allow for future
autonomous control development.

A printed circuit board (PCB) motherboard was designed to integrate all
onboard sensors with the TS-7800 single board computer (SBC). The board
allows proper powering of the sensors and data communication. It also
17
contains the electrical structure to drive the vehicle’s lifting mechanism and
communicate with the motor controllers.
2. Sensor Integration and Testing

The electronics system is capable of logging sensor data and was designed to
be further developed into an autonomous control system. This autonomous
system is currently in development at FAU by FAU graduate student Jose
Alvarez.

Each sensor was calibrated and tested individually to ensure it could collect
and save data.

The sensors were tested as a system to confirm all data was collected and
saved successfully for planned testing and future autonomous development.
3. Vehicle Behavior

Experimentally defined vehicle’s behavioral characteristics and capabilities
in the regions it must perform: land, sea and the transition region. This
included maneuvering characteristics in open water and land, as well as
forces, motions and accelerations experienced in the surf zone. Course
keeping was also tested, and power differences between port and starboard
motors for land and sea were found to allow the vehicle to track a straight
course, and make symmetric turns.

Determined the limitations of the model, such as: minimum turning radius,
maximum traversable gradient, maximum accelerations and velocities in the
different operating areas, limitations in a sandy environment, rate of turn for
18
a variety of virtual rudder deflections etc. This information has been
documented for reference for future research using this vehicle, so tests can
be designed to stay within the limitations of the vehicle model.

Motor inputs and vehicle outputs were defined by experimental testing. A
wide range of motor commands were given to the motors both on land and in
water and the response of the vehicle was measured with the on board
sensors.

The vehicle was tested in the surf zone to define the motions it experiences
during its transition between land and sea. These motions were related to
wave characteristics. The drivetrain forces experienced in this transition
were also found by tests in the surf zone compared to dynamometer motor
tests.
4. Vision System

A vision system has been initially developed and tested using OpenCV
computer vision open source software. The system is capable of providing a
control system with information about the vehicle’s surroundings and the
locations of potential obstacles or navigation buoys. This will be used in
future development of the DUKW’s autonomous navigation system. This
system information is included in the appendix.
5. Universal Control System

The sensor and control system, and especially the motherboard PCB, were
designed in such a way that they can be used with other similar projects.
19
This project studied similar efforts in the past as well as the future at FAU
and developed a system based on some of the requirements found most
frequently on autonomous vehicles. This is in hopes that future projects can
build on the progress made in this thesis work.
The following document provides a detailed description of the complete system design,
the experimental approach taken for data collection, and a results section that presents
the data with discussion of the results.
20
2
2.1
APPRO
OACH
Modiffication, Upg
grades and System
S
Desiggn
The vehicle
v
was equipped with
w a basic sensor systeem in 2010 during the FAU
senior desig
gn project. The
T sensors used were nnot adequatee for the plaanned researrch or
control systtem developm
ment. It wass determinedd the sensor system musst be upgradded to
meet the acccuracy requ
uirements in the plannedd research. T
The modification and syystem
design will be
b detailed below.
b
The mechanicall system off the initiall demonstraator model, specificallyy the
w deemed
d unusable by a past project, andd needed too be replaceed to
drivetrain, was
continue dev
velopment of
o this conceept. The moddel was originally built w
with a five w
wheel
drivetrain and used inadequate gear ratioss that show
wed poor results in land
ng, and the vehicle
v
was unable
u
to peerform in saand. The mechanical chaanges
maneuverin
done in this work added
d a tank track drivetrain that allowedd the vehiclee to perform
m well
in land testiing. Motor mounts,
m
chaain drives annd gear systeems were allso redesignned in
order to provide a working vehicle capable
c
of p erforming planned testinng.
2.1.1
Mecchanical Con
nversion
The original traccked drivetraain design, ddeveloped at CISD, wass the basis oof this
design. Thee maneuveraability of a tracked
t
vehiicle is propoortional to tthe ratio of track
length in contact with
w
the ground,
g
to distance bbetween trrack centerrlines.
221
Maneuverab
bility is meaasured by th
he ease of stteering and ccourse keepping. The opptimal
ratio is betw
ween 1.3 and
d 1.8, with lower
l
ratios causing unsstable condiitions, and hhigher
ratios causiing difficultty in steering [20][13]]. The sepaaration of tthe model’s hull
centerlines is 32 inchess, which meeans the tracck length shhould be bettween 40 annd 57
inches. Befo
ore modificaation, as sho
own in the ffigure below
w, the ratio w
was too highh and
the vehicle was
w unable to
t turn.
Fiigure 4 - Origiinal Vehicle w
with Wheel Drrivetrain
In order
o
to sim
mplify the orriginal modeel design, thhe tracked ssystem origiinally
proposed fo
or the DUKW
W 21 was reeplaced withh wheels forr the originaal construction of
the model, as seen in figures
fi
4 and
d 5. This redduced constrruction costt and compleexity,
but also lim
mits testing an
nd the model’s capabilitiies.
222
The existing land-based propulsion system on the vehicle was found to be
inadequate by the 2010 FAU senior design project [32]. This project attempted to
operate the vehicle between water and a sandy beach. They were unsuccessful in
operating the vehicle on the beach due to issues with the original drivetrain. This project
was therefore restricted in the tests it could perform.
There are two problems the previous project documented in terms of the land
propulsion. First, the front and rear wheels would drag when the vehicle performed a
turning maneuver, and therefore limited the testing that could be done with the vehicle,
while also putting added strain on the motors and drivetrain. The high length-toseparation ratio explains this problem. In a turning maneuver, the vehicle was actually
held back by its front and rear wheels. The second issue with the original drivetrain was
the chain driven sprockets. Being an amphibious vehicle, the DUKW-ling frequently
encounters a sandy environment during testing and operation. The original drivetrain
consisted of a drive wheel that was linked to each of the other four wheels with a chain
and sprockets. However, the sprocket radius was 10 [cm], while the wheel radius was
13 [cm] This configuration can be seen in figure five below. In sand, the wheels sank as
the vehicle maneuvered, causing the sprockets to be submerged in the sand, which
bound the drive system as sand was spun into the chain and sprockets. Lubrication of
the steel chain was also difficult because of its location inside the hulls, and it had
significant rust and corrosion damage. This damage increased the torque required to
move the vehicle, due to the fact that the chain was over 3 meters long and drove five
separate sprockets. The gear ratios used to drive the wheel drivetrain were also incorrect
23
and required
d a high amo
ount of torqu
ue on the mootor sprocketts.
Figure 5 – Original
O
Five W
Wheel Drivetrain
It was determineed the ideal modificatioon of the vehhicle was too convert thee five
wheel, conttinuous-chaiin driven drrivetrain intto a tank trrack system, which is more
similar to th
he full scale design, and
d would perfform better than tires inn the sand. IIn the
new configuration, there is no ch
hain near thee sandy groound. The ffront drive chain
controls the main drive sprocket forr the track syystem, and is over 25 [cm] from thee sand
at its lowest point. Thee chain was also increassed in size, so sand woould not affeect its
operation. The
T new chaain is shown
n in the figuure below oon the left, with the oriiginal
chain on thee right for co
omparison.
224
Figure 6 - New Chain
n vs. Original
The front and rear
r
track sp
prockets werre raised froom the bottoom-most whheels,
which easess the turning
g of the vehicle, since it will no longger have to ddrag its fronnt and
rear wheels,, as it did with the previious drivetraain. This connfiguration iis called a doouble
ramped tracck, and allow
ws the vehiclle to both appproach and ddepart largerr obstacles tthan a
single or no
o-ramp confi
figuration. Th
his also reduuces the tracck length inn contact witth the
ground, providing a low
wer ratio, and
d better drivve characteriistics becausse of its increeased
maneuverab
bility. The neew design usses the lowe st ratio, a traack length off 1.01 [m], w
which
makes the vehicle
v
most maneuverab
ble as descriibed above. T
This value ccan be adjustted in
the future by
y adjusting the
t mounting positions oof the front and rear whheels up to a track
length of 1.12 [m]. Thiss adjustment would give a ratio of 1.38, as shownn in figure 77.
225
Figure 7 - Tracked Vehiclee Separation R
Ratios
The new drivettrain attachees to the cuurrent frame of the vehhicle, with m
minor
modification
ns and addeed axle bracckets. The aangle the froont and rearr sprockets m
make
with lower wheels are such that hu
ull damage iis avoided w
when approaaching an inccline.
minum drop
pdown brack
ket is show
wn in figuree eight. CA
AD drawingss and
The all-alum
pictures of all
a fabricated
d parts are in
ncluded in thhe appendix.
Figurre 8 – Tracked
d Drivetrain
226
The configuratio
on of the traack system iimproves peerformance iin turning, speed,
resistance and max grad
dient capabilities. The w
wheel positioons are alignned to protecct the
front and reear of the veehicle hull from
f
comingg into contaact with beaach gradientss and
obstacles. The
T angle beetween the lo
ower wheelss and the driive sprockets is 68 [degrrees].
This angle determines the range of obstacle s the vehiccle is capabble of traverrsing.
Because this is a non-co
ombat, cargo
o transport vvehicle, the oobstacles thaat will be prresent
are assumed
d minimal, so
o the angle was
w not a larrge factor in the design. While there is no
documentatiion of the track
t
angle in the origginal design of the DU
UKW 21 vehhicle,
pictures of the
t vehicle in
n a report sh
how an anglee less than m
most combataant tank tracks.
Figuree 9 - Conveyorr Belt Track
The track used in the desig
gn is an Aceetal plastic cconveyor beelt from Intrralox,
seen in figu
ure 9 above. Plastic strip
ps were addded to replacce the rubbeer friction toop for
increased trraction in saand. A track
ked drivetraiin will allow
w for better estimates oof the
full-scale vehicle’s
v
beh
havior sincee it will be more simillar to the ffull-scale traacked
design. Thee bottom six
x wheels carrry the loadd of the vehhicle, and thhe front andd rear
sprockets keeep the track
k in place. Th
he front sproocket is driveen by a chain and gears
227
using an electric motor mounted on the above superstructure.
The gearing and motor size were determined by attaching a load cell to the
vehicle in many different situations that would be expected in testing in the beach test
area; inclines, as well as soft sand, hard packed sand, and partially submerged vehicle
were explored to find the force required to move the vehicle from rest. The maximum
resistance measured in these tests was used in determining the ideal gearing of the
motor and chain drive system, using a 20% margin of error added to the maximum
measured resistance. The maximum rolling resistance was found when the vehicle was
partially submerged in the surf zone. 890 [N] of force was the maximum measured
force required to move the vehicle in this area. So a resistance of 1,068 [N] was used in
gearing calculations, assuming this is the worst case scenario to be encountered. Results
of the rolling resistance tests in different situations can be found in the results section.
A dynamometer was used to understand the motor characteristics, because no
documentation was available from the manufacturer. The torque available from the
motors was important in choosing gears to drive the new drivetrain. The dynamometer
allows torque to be manually adjusted, and also has software that can subject the motor
to user-defined tests. The motor controllers were used in the tests, so torque could be
related to the current to the motors and motor commands, which are both measured by
the motor controllers. The results of the dynamometer tests can be found in the results
section. These results were used for drivetrain gearing and sprocket choices.
28
Figure 10 - FB
BD of Vehiclee Rolling Resisstance
Now
w that the provided
p
motor
m
torquee was deterrmined, the gears coulld be
determined to overcome the resistaance measureed, while allso minimiziing the torquue on
the motors and
a providin
ng adequate speed of thee vehicle. Thhese three faactors were ttaken
into consideeration for th
he design. Th
he forces accting on the vvehicle are sshown in thee free
body diagraam above.
The diagram below illustrrates the spprocket num
mbering systtem used inn the
gearing tablle. The left figure
f
is abo
ove the hull aand the rightt figure is beelow the hulll and
shows the drive
d
axle with
w the fourtth sprocket and the drivve sprocket which drivees the
tank tracks.
229
Fig
gure 11 - Gearring System N
Numbering Coonvention
The worst case force
f
of 1,06
68 [N] (seenn as half of thhis value in the table beccause
there are tw
wo motors) was
w used as th
he force on the track driive sprockett, and becausse the
radius of th
his sprocket was fixed, 47.5 [Nm] of torque rrequired froom the driveeshaft
could be deetermined. This
T
torque is
i equal to thhe torque reequired by ssprocket fouur, the
chain driven
n sprocket on
o the same axle, in ordeer to move tthe vehicle tthrough the w
worst
case scenariio. Sprocketts three and four were addjustable in the design. The force oon the
chain and th
he angular velocities
v
off each shaftt would varyy as the sprrocket sizes were
changes.
ues, forces aand tangentiial velocitiess were show
wn at
The table shows that torqu
each point in the drive system,
s
and varying the two sprockeet sizes show
wn outlined iin red
mbinations of
o speed, forrces and torqques until ann adequate ddesign
would give different com
was found.
330
Table 2 – Gearing Equations
Gearing Table Variables and Equations
Rotations Per Minute
∗ 60
Rotations Per Second
Circumference
2
Tangential Velocity
Force
Torque
∗
Radius
31
Figure 12 - Gear Sysstem Torques
Belo
ow is a table that was used to find alll torques, foorces, speedss, RPMs andd gear
sizes of the new track drivetrain, and
a was useed to adjust the design uuntil an adequate
combination
n was found..
Table 3 - Gearing Spreadsheeet
Radius [cm]
RPM 1
RPS 1 Circumference [cm]
Tangential Vel. 1 [m/seec]
Force 1 [N]
Torque [Nm}
1.27
2600.00
43.33
7.98
3.46
306.25
3.89
Radius [ccm]
5.64
4 Radius [cm]
RPM 2
585.59
9 RPM 3
RPS 2
9.76
6 RPS 3
Circumfeerence [cm]
35.43
3 Circumference [cm]
Tangentiial Vel. [m/sec]
3.46
6 Tangential Vel. [m/secc]
Force [N]
306.25
5 Force [N]
Torque [[Nm}
17.27
7 Torque [Nm}
2.92
585.59
9.76
18.35
1.79
591.19
17.27
Radius [cm
m]
8.03 Radius [cm]
R
RPM 4
213.11 RPM 5
R
RPS 4
3.55 R
RPS 5
Circumfereence [cm]
50.43 Circumference [cm]
C
Tangential Vel. [m/sec]
1.79 Tangential Vel. [m/sec]
T
591.19 Force [N]
F
Force [N]
Torque [Nm
m}
47.45 Torque [Nm}
T
8.89
213.11
3.55
55.86
1.98
533.76
47.45
A fo
our sprocket drive system
m was chosenn because off the high RP
PM of the m
motors
and the high
h torque requ
uirement forr moving thee vehicle. Thhe configuraation allows for a
large gear reduction,
r
ab
bout 7:1, wiithout the usse of a com
mplex worm gear. The m
motor
sprocket haas a one 2.5
54 [cm] diaameter whille the final tread drivee sprocket hhas a
diameter off 17.27 [cm]. The chain that drives tthe drive axxle is #50 rooller chain, w
which
332
has a pitch of
o 1.6 [cm], and working
g load of 6855 [N]. In thee table show
wn, it can be nnoted
this working
g load satisffies the forcee calculated on the chainn in the preddicted worstt case
scenario. This
T
chain is 2 [cm] in
n width so sand does not signifiicantly affecct its
performancee. All sprocckets, chain and drivetrrain componnents are sttainless steeel for
corrosion reesistance.
2.1.2
Elecctrical, Senso
or and Contrrol System D
Design
Belo
ow is a blocck diagram of the vehiicles electroonics layout.. The waterpproof
electronics box
b is located on top of the vehiclee super struccture, and thhe hull boxees are
attached to the
t top deck
k of each hulll. The starbooard box conntains a mottor controlleer and
batteries forr the land motors,
m
and the
t port boxx contains thhe propeller motor contrroller
and batteries.
333
2.1.2.1 Single Board Computer (SBC)
The original model’s electrical system was upgraded to allow for improved data
acquisition and added systems integration. The control system was designed around an
ARM9 based Technologic Systems TS-7800 processor. The TS-7800 is mounted on a
new motherboard PCB and housed in the waterproof control box on top of the vehicle,
and is easily detached for bench tests and development, as well as transfer to another
vehicle. In order to isolate the control electronics from the noise generated by the
drivetrain and propeller motors, this control box has its own power supply. The TS7800 is used because of its processing capabilities, the number of serial ports and the
familiarity current FAU graduate students have with the system. Some of the notable
specifications of this particular board are its 500 MHz ARM9 processor, its twelve TTL
and RS232 serial ports, SD and micro SD card slots and a PC104 interface. The TS7800 uses a Linux operating system and its capabilities make it a good candidate for use
in a future autonomous control system.
2.1.2.2 Sensor System
Autonomous vehicles rely heavily on a GPS and compass for position and
heading measurements. To allow testing of the model, as well as autonomous
navigation, a sensor suite was added, which includes a GPS enabled Inertial
Measurement Unit (IMU), Differential GPS (DGPS), tilt compensated digital compass,
depth sensor and water sensors. There are also two motor controllers that drive the track
system and propeller motors.
34
The GPS enabled IMU is an XSens MTI-G, and uses accelerometers and
gyroscopes to measure accelerations, orientations and gravitational forces. This sensor
is important in measuring motions the vehicle experiences in the surf zone. The
Hemisphere V111 differential GPS is a conventional GPS that also uses land based
stations to correct any errors in location. It also has two GPS receivers so position data
can be compared to improve accuracy. This technique lowers the normal ten meter GPS
accuracy down to less than half a meter, based on manufacturer specifications. This
accuracy is critical in vehicle testing because any discrepancies in the GPS position
measurement would yield inaccurate results. An OceanServer OS5000 3-Axis tilt
compensated compass gives vehicle heading, with a manufacturer stated accuracy of 0.5
degrees. The compass is tilt compensated, and pitch motions can be recorded with this
sensor. These three sensors are all serial devices.
An RF transceiver is used for wireless communication between the vehicle and a
shore based laptop monitoring station. The unit used is a 900 MHz XStream OEM RF
transceiver module. This RF transceiver is mounted on the motherboard PCB and is
used to send data between the shore station and the onboard TS-7800 computer. This
provides a secondary source for data collection, in addition to saving sensor data
onboard the vehicle. It also provides a means of monitoring and ensuring proper
operation during testing and future autonomous navigation.
A depth sensor is used to monitor the water depth in which the vehicle is
operating. This is important in testing as well as navigation. During testing, the depth
was monitored to ensure sufficient depth was maintained, to avoid any discrepancies in
35
data due to bottom effeccts. In auton
nomous naviigation, it is assumed thee vehicle will use
depth sensor data to con
ntrol which means
m
of proopulsion it rrequires to kkeep its course. In
a similar reegard, water sensors weere installed on the fronnt and rear of the vehiccle to
detect when
n it has enterred or exited
d the water. T
The informaation from thhese analog w
water
sensors willl be used to
o control thee type of proopulsion thee vehicle is uusing. The w
water
sensors werre designed and built in house annd use a sim
mple circuiit located onn the
motherboard
d PCB. Th
he schematiics of the water senssor are shoown below. The
microcontro
oller sends an
a analog signal
s
to thee water sensor located at a part oof the
vehicle thatt would be submerged in the beachh transition. The sensorr consists off two
leads, and when
w
the cirrcuit is shorrted becausee it is in coontact with w
water, the sensor
notifies the control systeem using a digital
d
I/O linne.
Figure 13 - Water Sen
nsor Schematiic
The RoboteQ AX2550
A
mottor controlleers are a staandalone unnit located in the
battery boxees on each hull.
h
They are dual channnel motor coontrollers, soo they can coontrol
two differen
nt motors sim
multaneously
y. Because tthe vehicle hhas both landd and sea mootors,
336
these controllers were ideal for the application. They use either serial or remote control
communication, and are manually switched between the two depending on the
application. The motor controllers can be controlled with RoboRun software, which
allows bench testing, and the ability to operate the motors before installation on the
vehicle. This software was also helpful in dynamometer testing. The software outputs
voltage and current, and can also be used to record this information during testing.
RoboServer is another software function provided with the motor controllers.
RoboServer allows wireless communication between a host and server laptop. This
allows a server laptop to be onboard the vehicle running the RoboServer software and
connected to the motor controller via a serial port. The host computer runs the RoboRun
software remotely and sends commands to the onboard server laptop. This means the
RoboRun data collection and motor command software can be controlled on-shore,
while the vehicle navigates in the water, as seen in figure sixteen. This proved to be a
very useful tool in testing, allowing data collection and adjusting motor commands
wirelessly using the motor controller software. Below is a figure provided in the motor
controller manual that explains how this function works.
37
Figure 14 – RoboteQ’s RoboSerrver Software Operation
Wheen the motorr controllers are being ussed without tthe manufacctures softwaare
during testin
ng, data is trransmitted viia the serial lline in a hexxidecimal strring. Below iis the
layout of thee data string
g, and the Maatlab sectionn of the appeendix shows how this datta
was read an
nd plotted verrsus coordin
nated UTC tiime to syncrronize motorr data with seensor
results.
Figuree 15 - Motor Controller
C
Hexxadecimal Com
mmunication
338
A fo
orklift style cargo hand
dling mechaanism below
w was designned by the FAU
senior desig
gn project teeam in 2010, and uses a winch, lineear actuatorss and momeentary
switches to control the lifting
l
and lo
owering of th
the arms. Thhe vehicle’s ccargo mechaanism
was designeed to securee a 1/7th scalle ISO conttainer for traansport. Thee system reqquires
minor electrrical circuitrry and this was
w added too the new electrical sysstem so the ccargo
handling mechanism
m
reemained fun
nctional. Thhe lifting system uses H
H-bridges, w
which
allow for multi-directio
m
onal power,, for the abbility to opeerate the ellectric motoors in
forward or reverse
r
with the same cirrcuit.
Figure 16 – Container Liifting Mechan
nism
2.1.2.3 Mo
otherboard PCB
P
A prrinted circuitt board (PCB
B) was desiggned as the m
motherboard which bringgs the
electronic sy
ystem togeth
her to interfface with thee TS-7800 ccomputer. Alll vehicle seensors
are either mounted
m
on the board, or plug intoo the board from other locations on the
vehicle. A PCB
P
simpliffies the wiriing and circuuitry neededd to interfacce all sensors and
vehicle systtems. A high
h level block
k diagram off the sensorss and their iinterface witth the
TS7800 is shown below
w.
339
Figure 17 –C
Control Syste m Block Diaggram
The motherboard PCB was designed annd fabricatedd in house. T
The PCB conntains
y needed to operate thee vehicle inn testing andd during fuuture autonom
mous
all circuitry
navigation. The vehiclee’s IMU, com
mpass, RF T
Transceiver and RC recceiver are loocated
inside the waterproof
w
ellectronics bo
ox, and are mounted onn the PCB. T
The DGPS, ddepth
and water sensors,
s
two motor conttrollers, and lifting mecchanism are found outside of
the electron
nics box and are wired to
o the PCB th
through wateerproof bulkkhead connecctors.
Each sensorr or vehicle component has its uniqque circuitry required for power andd data
transfer prin
nted on the board.
b
This circuitry
c
wa s designed, laid out on tthe PCB andd sent
for printing. Because each
e
sensor has
h specificc power requuirements, aand its data, both
sent and recceived, musst go to a sp
pecific port on the TS--7800, the P
PCB significcantly
reduces com
mplex wiring
g requiremen
nts by printinng it on a 333x20 [cm] bboard. All veehicle
componentss plug directlly to the boaard in a certaain location and the circuuits that inteegrate
440
each with the entire system is located on the PCB. Many different test points were
added to the board layout to simplify debugging and testing. Because there have been many autonomous vehicle research projects at FAU in
recent years, an attempt to make a universal sensor and control system was made in this
project. This would make the development of future projects a concentration of
software, as opposed to sensor, electrical and hardware development, which was a large
time consuming task in this, or any project. A PCB motherboard layout can take many
weeks or months to design and draw schematics and board layouts, and many times
these boards are very similar from vehicle to vehicle. The focus of the universal
capabilities was in the electrical system and the integration with the SBC. Previous
projects were taken into consideration when designing the control system on the
DUKW-ling. This mainly dealt with the addition of capabilities that are usually
necessary on similar projects, such as extra analog inputs and spare serial lines easily
accessible on the PCB motherboard.
The PCB was designed to provide the user with as many options as possible in
sensors that could be used with this board. For serial communication, all RS232 serial
ports were accessible through uniform plugs on the board. This allows any combination
of sensors to be interfaced with the computer, and also helps in software testing and
debugging. Even serial lines that were not used in this particular project were made
available on the board. Three H-bridge circuits were included on the board for
supplying power to various systems on future vehicles. In this case, the three H-bridges
power the lifting mechanism’s winch and linear actuators. H-bridges allow voltage to be
41
provided to the circuit in either direction, which makes them ideal for controlling
electric motors in forward or reverse.
A series of digital inputs and outputs were also made easily accessible through
plugs on the PCB. Because these digital input/output lines are so general, and can be
used to a variety of different applications, having access to them through the PCB will
be useful for any project. In addition to the digital lines, twelve analog ports were made
available through the PCB. Three of them are designated monitoring ports for battery
voltage, current and H-bridge voltage. The board was designed to pass six of these
analog lines through amplifiers, which provide either five or twelve volts. These
amplified analog signals can be used for a load cell or other analog sensor frequently
used in autonomous vehicle development.
An RC receiver was paired with a Pololu Maestro twelve channel servo
controller in order to provide the option of controlling onboard servos remotely. This
increases the usefulness of this board because of the amount of systems that can be
controlled using a remote control, which is often performed in autonomous system
development. The wiring diagrams and PCB layout diagrams can be seen in the
appendix. Below is the developed PCB motherboard before it was installed on the
vehicle. The red stack of two boards is the TS-7800 CBC board and the analog-todigital converter board. The IMU and compass are mounted on the board but are not
pictured below.
42
Figure
F
18 - PC B Motherboaard
2.2
Experrimental App
proach
Testting was peerformed to verify thaat the improoved vehiclle is capable of
performing in the operaational envirronments thaat its missioon will exposse it to, landd, sea
urf zone beetween the two, and too characteriize the vehicle’s
and the traansitional su
behavior fo
or future research and development
d
t. In this higghly dynam
mic surf zonee, the
forces and response
r
chaaracteristics of
o the vehiclle need exploration throuugh experim
mental
testing. Dettermining the forces and
d behavior oof the vehiclle in this traansition regiion is
the first step
p in develop
ping adequatte models foor control off an autonom
mous amphibbious
vehicle.
The testing con
nditions werre mainly ddriven by thhe terrain aavailable at FAU
Seatech and
d the Daniaa Beach coaast. For landd testing, thhe original rrequirement of a
gradient of 1/50 was inccreased to 1//5, or about 10 [degreess], the averagge gradient oof the
w
was measured
m
witth a clinomeeter. The m
main fluctuatting parametter in
test area, which
water-based
d testing waas the weath
her, more sppecifically thhe waves prresent in thee surf
zone, which
h could not be dramaticc because o f the size oof the vehiclle model. D
During
443
initial vehiccle testing, th
he maximum
m wave heighht and surf cconditions foor operation were
defined, so testing
t
could
d be limited to conditionns within theese parameteers.
The waves weree scaled geo
ometrically based on thhe 1/7th scalle of the veehicle
model. The wave frequeency, howev
ver, was scalled using thee equation bbelow, wheree T is
wave period
d [29].
√
Sea state limitattions were a restriction oon test condditions. The m
model was ttested
nditions up to
o sea state one.
o
Sea staate 1 (SS1) iincludes waaves less thaan 0.3
only in con
[m], with a period of 2 seconds. The
T wind sp eed is between 2.57 - 44.16 [m/s], aand a
wavelength of 3.04 - 4.8
88 [m].
2.2.1 Senssor and Test Equipment Calibration
IMU
U: The Xsen
ns IMU wass calibrated using softw
ware providded with thee unit
which comp
pensates forr disturbancces in the m
magnetic fieeld measureed by the IM
MU’s
magnetometters. It is im
mportant not to
t expose thhe sensor to strong magnnetic fields aat any
time becausse non-magn
netic parts insside the unitt may becom
me magnetizeed as a resultt.
Becaause the mag
gnetometers on the Xsenns IMU use tthe earth’s m
magnetic fielld for
operation, disturbances
d
s in this fieeld will cauuse inaccuraate results. D
Disturbances are
typically ch
haracterized in two cattegories. Diisturbances that are inntroduced byy the
sensor’s surrrounding en
nvironment are
a random and cannot be predictedd. An exampple of
this type of disturbance is if the DU
UKW-Ling w
were to pass an oncomingg boat contaaining
444
ferrous materials. These non-deterministic disturbances cannot be compensated for in
advance. Therefore, a Kalman Filter running in the DSP reduces these types of errors.
The second type of error is called hard or soft iron effect. These disturbances
can be compensated for prior to testing because they are a direct result from objects that
move with the IMU sensor. Hard iron disturbances are caused by permanent magnets,
while soft iron is metallic parts such as vehicle structure, drivetrain, etc. The error in the
magnetic field is a function of the orientation of these objects to the sensor, and can be
predicted. These deterministic effects are compensated for by calibrating the sensor
prior to testing. As long as the orientation of the sensor and its surroundings is constant
(the vehicle’s components are not changed and batteries, motors, etc. are not moved),
the calibration will yield accurate results.
In an ideal, non-disturbed magnetic field, the 3D measured magnetic field vector
has a magnitude of one. Therefore, all measured point would lay on the circumference
of a sphere with a radius of one and a center at zero. When disturbances are introduced,
this sphere is shifted and warped. Assuming there are no non-deterministic errors
causing this distortion, the sensor can be calibrated prior to testing to compensate for
the warping. This calibration compensates for any deterministic, hard or soft iron
effects, such as the vehicle’s motors, electronics, structure, etc. Because there is no way
of differentiating between the two types of disturbances, it is important to calibrate the
vehicle away from external disturbances that could distort the magnetic field, so that
any disturbance during the calibration is caused by objects moving with the IMU on the
vehicle. The Xsens user’s manual recommends the IMU be at least three meters from
45
any ferromagnetic objects in order to ensure a homogenous magnetic field for
calibration.
To calibrate the sensor, it is placed in the location it will be during data
acquisition, with all vehicle systems in place. The IMU data is recorded using the Xsens
software. The vehicle is rotated 360 [degrees], at a speed that completes one rotation in
three minutes, and the magnetometers collect data. Because the only interference is
from on-vehicle noise, any warping or distortion in the data is a direct result from this
hard or soft iron effect. Therefore, because the same interference can be assumed during
testing, the calibration process will map the warped and distorted data into the sphere
discussed above. This “magnetic field mapping” technique is carried out using the
Xsens software and calibration parameters are determined and can be saved on the
sensor for future use, and calibration of test data. The magnetic field mapper is shown
in figure 21 below. It can be seen that the blue distorted field is calibrated in such a
way that the red, post-calibration map is symmetric and not distorted. The calibrated
accuracy is now 0.7 degrees, and the deviation goes from 8.5% to under 0.5%. This
process is also outlined in the Xsens IMU manual.
46
Figure 19 - Xsens Magneetic Field Map
pper
Com
mpass: Comp
pass calibrattion is ratheer straightfoorward and iis similar too that
performed for any oth
her magneticc compass. The compaass, like thee IMU, muust be
ms in place. The
installed in its permaneent location on the vehiicle with all other system
compass is set to a caliibration mod
de using an RS232 com
mmand: 0x1bb 0x43. It iss then
degrees] at a speed of ab
about one rootation per m
minute. After this
rotated in a full 360 [d
procedure, the
t calibratio
on constants are saved too the sensor,, although thhis proceduree was
carried out at
a the beginn
ning of every
y day the vehhicle was ussed for experriments.
Afteer the initiall calibration
n, a soft iroon calibratioon was perfoormed. Softt iron
compensatio
on deals witth disturbancces from meetallic materrials on the vehicle. Annother
command is
i sent to th
he compasss to enter ssoft iron callibration. U
Using a maggnetic
compass in
n an area frree of otherr magnetic disturbancess, the vehiccle is aligneed to
cardinal poiints: north, east,
e
south, west.
w
This caalibration prrocedure willl compensatte for
447
the effects of metal material on the vehicle, and is described in detail in the OS5000
Compass manual.
Dynamometer: The Magtrol DSP6000 controller and dynamometer can be
calibrated using two different methods. Both methods are “closed box” calibrations,
meaning all adjustments can be made using the dynamometer controller’s display panel.
The first calibration technique adjusts the torque readout and auxiliary input. The
calibration is carried out using an external reference voltage supply and a digital multimeter (DMM). The DMM should have an accuracy of 0.05% or better. The calibration
procedure was performed prior to any testing, and is recommended at least once a year,
or after any modifications are made to the system.
The DSP6000 was turned on for thirty minutes before any calibration was
performed. The DSP6000 was then switched to calibration mode by turning the
instrument off, pressing and holding the up and down arrows on the display. Torque
offset and gain is performed with the external voltage source. The ground is tied to pin
thirteen and positive to pin fourteen of the DSP6000. A voltage of two VDC is applied.
The gain is adjusted until the display voltage equals the two VDC reference voltage.
Then a voltage of zero is provided and the procedure is repeated. Calibration results are
saved on the instruments non-volatile memory for future measurements.
The second calibration procedure is dynamometer specific, rather than a
calibration of the DSP6000 instrument. This procedure must be performed if the data
acquisition DSP6000 unit is used on any other dynamometer. A calibration beam is
provided with the dynamometer and used in this procedure. The beam is attached to the
48
dynamometter shaft, and
a
the co
ontroller is switched to calibrattion mode. The
dynamometter brake is turned
t
on, an
nd a known w
weight is huung from thee end of the bbeam
at a pre-marked distancce. Because the distancee and weighht provides a known mooment
on the dynaamometer, the
t torque on
o the DSP66000 controoller can be adjusted unntil it
equals the known
k
input moment cau
used by the hhanging onee pound weigght, shown iin the
figure below
w.
Figure 20
0 - Dynamomeeter Calibratioon
2.2.2
Vehiicle Tests
Driv
vetrain conversion improved the caapabilities of the vehiclle; previous tests
using the original vehicle drivetraiin could not explore thhe vehicle’s transition tto the
beach becaause of the limitations associated with the ffive-wheeledd drivetrain. The
vehicle upgrades alloweed testing in
n this area off interest. Teesting begann with qualittative
tests to undeerstand the abilities
a
of the model w
with its new ddrivetrain. U
Understandinng the
449
operational limitations of the vehicle and the performance of the new drivetrain were
necessary for this project, as well as future projects that propose further testing of the
model. The model was operated by remote control in the different environments it was
required to operate. The main reason for these initial tests were to locate any problems
with the new vehicle system before any performances tests were conducted. Limitations
of the vehicle, such as the maximum incline it could climb, approach and departure
angles, rough estimates of its turning radius both on land and sea were noted so that test
plan development could take these parameters into consideration. An estimate of the
maximum wave height the vehicle could encounter was also determined to limit any
testing that could damage the vehicle.
As software was written, each sensor was tested for proper data collection and
storage. Initially, both a turning circle test and random zigzags were performed while
collecting data from each sensor independently. Because of the predictable motions of a
constant circle or alternating headings, sensors such as the compass, DGPS, compass
and IMU were tested with this method to verify they were collecting and saving data
with the onboard computer. Quickly plotting the collected data could verify if the data
was relevant to the specific test. The software was also designed to save its data onto a
USB drive, as a backup data collection tool and a way to transport it to a laptop. These
tests were also used to test the motor controllers. They would save information during
the test such as motor commands, current and voltage as well as internal temperature.
Once all sensors were collecting and properly saving data, more complex testing
was planned. A description of each area of testing is shown below with a description of
50
the test, the equipment needed and a descriptioon of the areea the test w
was performeed, as
well as any other relevaant information for each ttest.
2.2.2.1 Ro
olling Resistaance Testing
g
The rolling resisstance tests were
w the firsst tests perfoormed on thee vehicle afteer the
drivetrain was
w complette. These tessts were criitical for prooper drivetrrain gearing.. The
motors weree removed from
f
the veh
hicle, and thhe tracked vvehicle was pulled by a load
cell until itt began to roll.
r
The lo
oad cell wass set up to record the maximum force
measured. The
T sensor was
w initializeed when the ttow line was held taughht, and the puulling
force was slowly increaased until th
he vehicle beegan to roll. This test w
was perform
med in
different areeas of the beeach, on wett sand (pictuured below), dry sand, upp inclines ass well
as partially submerged. The resultss of this testt can be seeen in the ressults section. The
f
measu
ured in these tests was used to deetermine thee correct geearing
maximum force
required forr the vehiclee’s drivetrain
n; an additioonal twenty percent marrgin of errorr was
added.
Figure 21
2 - Rolling Reesistance Tests
551
2.2.2.2 Maximum Incline and Approach/Departure Angles
Approach and departure angles are the maximum angles of obstacles the vehicle
can encounter without dragging its hulls. The tank track drivetrain was designed to
maximize these angles, by lowering the track below the hulls to avoid contact with the
ground in most expected situations. These angles were found on flat ground using an
inclinometer.
The maximum incline the vehicle is able to traverse on sand was also found
through experiment. The current to the motors was measured during this test to
understand the strain put on the electric motors during these large incline situations.
This test helps define a safe operating limit for the vehicle when planning tests and
vehicle operation. While the vehicle may be able to traverse a large incline, the duration
of this slope should be limited based on the measured current to the motors. An
increased power draw to the motors for an extended period of time can damage them. A
variety of inclines were tested to show the current draw in the motors to help avoid
damage in testing as well as during autonomous navigation.
2.2.2.3 Land Maneuvering Characteristics
Minimum turning radius: the minimum turning radius on flat sand was
measured. Because the vehicle can also turn on axis by putting one track in forward and
one in reverse, this test ensured both tracks were in motion to find the minimum turning
radius while keeping forward momentum, and not pivoting on its axis. The GPS was
used to measure the position of the vehicle. The radius was also measured by measuring
52
the diameterr of the circlle the vehiclle traveled dduring the tesst. The test w
was perform
med in
both directio
ons. The veh
hicle is show
wn in the testt area in figuure below.
Figure 22 - Vehicle Duriing Land Testting
Maxximum Veloccity and Accceleration: T
The vehicle was tested oon flat sandd, and
the GPS an
nd IMU weere used to measure thhe vehicle’s maximum accelerationn and
velocity. Th
he motor con
ntrollers werre also usedd to record thhe motor coommands, cuurrent
and voltage to the motorrs as the testt was perform
med.
Moto
or Command
d Testing: These
T
tests aare a traditioonal turning circle maneeuver,
but perform
med over a range of viirtual rudderr deflections. Because the vehicle uses
differential thrust as op
pposed to a traditional
t
ruudder, a virttual rudder rrefers to diffferent
combination
ns of thrust between
b
the port and staarboard motoors. An equaation for deffining
a virtual rud
dder is show
wn below, wh
here
is thee rotations peer minute. B
Because this iis not
measured on
n the DUKW
W-Ling, the motor com
mmand was uused, becausse for the eleectric
motors the voltage
v
settin
ng is related
d linearly to R
RPM.
553
δ
|
|
A tu
urning circle test revealss tactical diaameter, advaance and trannsfer. Speedd loss,
roll angle an
nd peak/final yaw rates were
w also reccorded durinng these testss.
Figure 23 - ABS Turningg Circle Test [[39]
The different combination
c
s of motorr commandss were perfformed, andd the
vehicle’s response to th
hese comman
nds was meaasured. This informationn will be useful in
the develop
pment of au
utonomous control, as this input-ooutput data can be useed to
determine how
h
the vehiicle will reacct to differennt motor com
mmands to pperform diffferent
maneuvers autonomous
a
ly. The yaw rate measurred in these eexperimentss can also bee used
for control system
s
devellopment.
554
The vehicle began with a straight forward motion until steady state is reached,
then different combinations of motor commands were given to each motor and the IMU,
GPS and compass measured the result of each “virtual rudder” command. The time the
vehicle was able to drive at steady state was significantly affected by the small size of
the test area, which was a limiting factor in these tests. Because this is a tracked
drivetrain and its reaction to different motor commands will be unique to the vehicle,
this information is important in the design of autonomous control. The table four shows
the different motor command combinations that were used in testing. The maximum
motor command is 127 (a hexadecimal value), but for simplification of test results, a
round value of 125 was used.
Table 4 - Land Motor Inputs for Motor Command Circle Tests
Motor Controller Commands: Land
Left Turn
Port Starboard
35
55
45
55
35
75
45
75
45
105
55
105
75
105
45
125
55
125
75
125
105
125
Right Turn
Port Starboard
55
35
55
45
75
35
75
45
105
45
105
55
105
75
125
45
125
55
125
75
125
105
The DGPS, IMU and compass were used to collect vehicle position, motions
and heading, and the rate of turn for each set of motor inputs was found, as well as the
turning radius for each case. This result of this test is a set of inputs and outputs specific
55
to the vehicle for different motor commands. A Matlab code was developed to parse the
GPS data, save the position coordinates and save them in Excel format, plot position
coordinates in Google Earth and Google Maps, as well as plot heading, velocity and rate
of turn (yaw rate), versus coordinated UTC time. The motor controllers were also used
to collect motor data during the tests. In the results section 3.1.1.4 below, the motor
controller data (system inputs) will be provided, along with the resulting system output,
or sensor data. The sensors will record information such as: velocity, yaw rate, position,
heading, roll, pitch and yaw. All sensors collected data with a UTC time stamp so all
data could be synchronized.
These tests give similar information as a standard turning circle maneuver as
described in [39]. However, a turning circle test only uses one deflection of the rudder
of about fifteen degrees, which only gives data for this single case. Because the goal of
this work is to provide a comprehensive set of data that is useful for autonomous control
system development, many combinations of motor commands were tested to give the
complete range of input/output relationships pertaining to the vehicle. This is in hopes
that the autonomous system can use this information to better control the vehicle as the
response to the full range of motor inputs is well defined.
2.2.2.4 Sea Maneuvering Characteristics
Minimum turning radius: The minimum turning radius was found in calm water.
As in land testing, the test found the minimum turning radius while keeping forward
momentum. A second test was also performed, pivoting the vehicle on-axis by putting
one motor in forward and one in reverse to determine the response of the vehicle. The
56
GPS was used to measure the position of the vehicle in both cases. The radius was
found by measuring the diameter of the circle the vehicle traveled during the test. The
test was performed in both directions.
Maximum Velocity and Acceleration: The vehicle was tested in calm water, the
GPS and IMU were used to measure the vehicle’s maximum acceleration and velocity.
The motor controllers were also used to record motor commands, current and voltage to
the motors as the test was performed.
Motor Command Testing: As in land testing described above, different motor
commands were given to the propellers after the vehicle was in steady state. The
vehicle’s responses to the motor commands were recorded by the IMU, GPS and
compass. Table five shows the different combinations of motor commands provided to
the propellers. The rate of turn and turning radius for each case was also found. The full
description of this test can be seen above in the land testing section.
Table 5 - Water Motor Inputs for Motor Command Circle Tests
Motor Controller Commands: Water
Left Turn
Port Starboard
0
80
‐40
80
‐80
80
0
100
‐40
100
‐80
100
‐100
100
0
125
‐45
125
‐85
125
‐125
125
Right Turn
Port Starboard
80
0
80
‐40
80
‐80
100
0
100
‐40
100
‐80
100
‐100
125
0
125
‐45
125
‐85
125
‐125
57
Thesse values aree different from
f
land tessting becausse the land ttest combinaations
did not prov
vide an adeq
quate turning
g radius. Thee vehicle had to utilize ddifferential tthrust
with one motor
m
in reveerse to prov
vide a relevaant turning m
maneuver. F
For examplee, the
combination
n of 75 and 45 used in the
t land testts would, in water, produuce a slight track
to one side, but not a turrning maneu
uver.
neuvering Tests
T
Man
Figure 24 – Autonom
mous Control
Figu
ure 23 showss a typical block diagram
m for the conntrol of a veehicle [11]. IIt can
be seen thatt understand
ding the vehiicle’s dynam
mics is an im
mportant stepp in controlliing it.
Because au
utonomous control
c
of am
mphibious vvehicles is a new area of researchh, the
dynamics of
o these typ
pes of vehiicles is pooorly charactterized, andd control syystem
developmen
nt requires experimenttal testing, modeling and validattion [36]. Most
important fo
or defining vehicle
v
dynaamics are syystems identtification, m
maneuvering tests,
performed while
w
collectting necessarry data.
Systtems identifiication is necessary for tthe developm
ment of autoonomous control,
and dynamiic behavior is
i unique to different veehicles [11].. The data acquired by oopen558
loop tests can be used to derive coefficients for maneuvering equations. Most of the
ABS recommended maneuvering tests were performed to characterize the dynamic
behavior of the vehicle. The maneuvering test performed with the DUKW-Ling are
described below.
Turning Circle Test: The traditional turning circle test is one of the most popular
tests performed in maneuvering trails. However, this test was combined with the motor
command tests in this work to provide a more complete set of data with more relevant
results. See motor command testing above for turning circle test results. The vehicle
was given a variety of different motor commands, or virtual rudder deflections, and
performed a turning circle test as well as a pull out test.
Pull-out Test: A pull out test is a classic maneuvering test that shows the
dynamic stability and course keeping ability of a vessel [39]. Pullout tests were
performed after completing each turning circle test, which reveals if the vehicle is
dynamically stable and able to keep a course. After the turning circle test, the virtual
rudder is returned to zero, or no deflection, with equal motor commands. The track the
vehicle takes after this command reveals the vehicles straight course keeping ability. If
it returns itself to a straight course after the rudder is returned to the neutral position,
then it is dynamically stable. It is important to understand the vehicle’s response in the
pull out test because a dynamically unstable vehicle must be controlled differently in
autonomous navigation than a stable vehicle. This course keeping ability was also
explored in the straight course tracking tests, and it was determined the “propeller walk”
59
of the vehiccle caused a dynamicallly unstable ssituation, whhich will bee discussed iin the
results section.
Zag Test: The
T zig-zag test is a sttandard testt performed in maneuvvering
Zig-Z
experimentss. It providess the vehiclee with alternaating rudderr commands and the vehicle’s
response, sp
pecifically its velocities and
a yaw ratee, are measuured. The tesst reveals heaading
and turning controllabillity. Typicall zig-zag testts use a ruddder deflectioon of ten deegrees
until a head
ding change of ten degreees is seen. In this testiing, becausee the vehiclee uses
differential thrust, fivee different virtual
v
ruddder deflectioons were ussed to proviide a
r
Thiss zig-zag tesst was perfoormed on laand as well as in the w
water.
variety of results.
Figure 26 sh
hows a typiccal zig-zag teest used in sttandard manneuvering tessts.
Figu
ure 25 - ABS Figure
F
Zig-zagg Maneuveringg Test [39]
The data collectted from theese zig-zag tests is usefful in system
ms identificaation.
Matlab’s Sy
ystems Identtification too
olbox was uused to estim
mate a modeel of the DU
UKW660
Ling vehicle based on the zig-zag test results. This model will be a good starting point
for the next step of the planned work on this vehicle, which is autonomous control
system development.
2.2.2.5 Dynamometer Testing
To determine the drivetrain forces experienced by the vehicle as it traverses the
surf zone region, the motors were characterized using a dynamometer. A Magtrol
dynamometer was available at FAU Seatech and could be used with minor
modifications. The results from dynamometer testing were also used to determine
proper gear ratios in the vehicle drivetrain design (discussed in section 2.1.1), in
addition to measuring required drivetrain forces in the transition zone. The
dynamometer tests were used to define an equation that related the current to the motors
to the torque output. This value was then used to relate the current to the motors to the
force on the tracks, by using the drivetrain gearing ratios described in section 2.1.1. This
allowed the force on the tracks to be measured by recording the current to the motors
with the RoboteQ motor controllers.
2.2.2.6 Transition Region Tests
The transition zone is the biggest uncertainty in this concept, and data on how
the vehicle performs in this zone is necessary for continuing this concept’s
development. The forces and motions the vehicle experiences in this region were
expected to be very different from those experienced on land or at sea, however no
experimental data is available for this type of terrain. In addition, understanding the
61
drivetrain control forces required to maneuver in the surf zone is important for full-scale
design [36].
A vehicle navigating through breaking waves in the surf zone is a demanding
task, and understanding the motions the vehicle will encounter in this area is important
for full scale vehicle development. The development of the autonomous control system
will also need to take these motions into account, making sure it can correct the course
fast enough in this highly dynamic region. While relating the motions to exact wave
height, period and direction is nearly impossible in an environment other than a wave
tank, the vehicle motions can be related to the measured wave characteristics, and the
results are mainly meant to be used to develop future tests that can utilize a controlled
test facility such as a wave tank. The fact that the waves in this region are breaking
waves further complicates the ability to accurately model the waves.
Defining the vehicle motions in certain wave heights and periods can be
beneficial in future test development as it provides a range of measurements that can be
expected in controlled tests, and testing procedures can be based on the results found in
this work. In addition to providing data on vehicle motions expected in the surf zone for
continued development of this concept’s autonomous system, the results provided in
this work will give future test developers data to base their experimental set up on for
surf zone experimentation, whether it is specifically this concept or a similar surf zone
traversing concept. Because this is a new area of research, there is no other way of
estimating these vehicle motions compared to different wave conditions, so
experimental data will be useful for future development in this surf zone area.
62
These motions also are also crucial in autonomous control system development
because they give engineers developing such a system a quantitative measure of the
variations in vehicle heading that the control system must adjust for. Variables such as
system gains can be estimated with the results of these tests, and give a data set which
can help predict proper control system design.
Another benefit to these tests is that they confirm successful operation of the
designed system in this area. The vehicle’s electronic system, sensor package, drivetrain
and initial code development could all be tested for proper operation as the vehicle
traversed this hazardous area, to ensure proper system design for later autonomous tests.
These tests were performed in the same fashion that would be expected in
autonomous navigation. The vehicle was driven through the surf zone with its tracks
engaged, then through the transition region and onto the beach. Its heading, motions,
position and motor data were all recorded as it made this transition. Measuring the
current to the motors gave data that could be used to define the drivetrain forces
required to navigate through the transitional surf zone area; a requirement of the
concept development. This was documented by CISD as a necessary data needed for
continued development. The dynamometer tests described above were performed to
relate the measured motor current to a torque output of the motors, which will be
described in the results. Knowing the torque applied at the motors can be related to a
force output on the tracks by the gearing table shown in section 2.1. A Matlab code was
written that takes the measured motor current from a test, then determines, from the
dynamometer results, the torque output of the motor. This torque output is then related
63
to the applied force on the tracks. This code can be found in Appendix 2, and will be
described in detail in Chapter 3.
A range of different motor commands were used in testing. Also recorded were
weather information and wave characteristics as the vehicle navigated through the
transition area. The vehicle was tested from very low speeds to full vehicle speed, not
only to define its characteristics in each situation, but also to define the best speed for
making the transition when the vehicle is autonomous. It will be important to define a
speed which lets the vehicle perform the transition between land and sea successfully,
while demanding the least amount of drivetrain strain. This speed can be used for
autonomous navigation as a design speed to navigate the transition zone. The motors
were run at 80, 90, 100, 110 and 125 for these transition tests.
64
3
3.1
RESUL
LTS
Vehiccle Tests
Afteer mechanicaal and electrrical system design andd fabrication,, the vehiclee was
tested in a variety of different tessts describedd above. Soome of thesse tests provvided
results only, while otherrs provide reesults that arre interpretedd and discussed below.
3.1.1
Rolling Resistan
nce Testing
Rolling resistance testing was
w used to determine tthe proper ggear ratio foor the
land propulssion system.. By testing the vehicle in the test zoone it wouldd be operatinng in,
and finding the maximu
um resistance experienceed, the geariing system ccould be desiigned
to allow thee vehicle to operate in this
t
area. Deesigning thee vehicle’s ddrivetrain geearing
system baseed on the maaximum resiistance forcee found in thhe test area w
would ensurre the
vehicle wou
uld be able to
o execute an
ny maneuver during systeem developm
ment and tessting.
665
Table 6 - Rolling Resistance Test Results
Flat Solid Ground [N] Hardpacked Sand [N] Dry sand [N] 10 Degree Incline [N] 18 Degree Incline [N] Partially Submerged [N] 155.69
146.79
155.69
151.24
151.24
146.79
164.58
146.79
155.69
151.24
146.79
173.48
155.69
480.41
498.20
435.92
515.99
444.82
507.09
489.30
480.41
418.13
489.30
515.99
524.89
524.89
524.89
551.58
667.23
667.23
685.02
640.54
711.71
760.64
729.50
685.02
765.09
747.30
711.71
578.27
551.58
524.89
515.99
529.34
542.68
520.44
529.34
520.44
489.30
515.99
511.54
560.47
765.09
800.68
685.02
685.02
733.95
756.19
765.09
711.71
707.26
716.16
702.82
760.64
711.71
524.89
542.68
711.71
889.64
889.64
596.06
747.30
667.23
720.61
707.26
760.64
725.06
662.78
The maximum resistance force found in experiments was about 890 [N], as
highlighted in table 6 above. This is almost double the average resistance found when
the vehicle was tested on hard-packed sand. The partially submerged tests took place in
a water depth of between 15 to 30 [cm]. This proved to be the highest resistance the
vehicle would experience, due to the fact it was not only driving through soft, wet sand,
but also had the added mass of the water to overcome in this region as it is accelerated
from rest. It will be seen in the transition test results shown below that this added mass
is also apparent in these tests. In the transition tests, the current to the motors, and
effectively the torque required to move the vehicle, drops off as the vehicle comes
ashore.
The maximum force of 890 [N] found in testing was used in drivetrain design,
with a 20% margin of error added to it or 1068 [N]. A proper gear ratio that provided
the torque required to navigate this area, while also keeping the current to the motor at a
safe operating level was found based on these results. This final gearing design was
provided in above in Section 2.1.1.
66
3.1.2
Loccating Vehicle Center off Mass
It was importantt to locate th
he vehicle’s center of m
mass becausee this is the point
in which thee vehicle’s motions
m
pivo
ot around. Thhis is importtant in both testing as w
well as
systems iden
ntification. To
T find the vertical
v
posittion of the center of masss, or the disstance
from the bo
ottom of thee vehicle to
o the positioon of the ceenter of masss, the penddulum
method waas used. Wh
hile collectin
ng data witth the onbooard IMU, the vehiclee was
suspended using
u
the daavit at the Seatech camppus. It was tthen displacced a small angle
and swung like
l a pendulum.
Figure 26 - Center of Maass Pendulum Test
The distance fro
om the top of the vehiclee to the pivoot point of thhe pendulum
m was
s
in thee figure abo
ove, and the IMU colleccted roll, pittch and yaw
w data
known, as shown
versus time. Because a pendulum has
h a straighhtforward eqquation relatting its frequuency
667
and length, it is easy to find the center of mass, or end of the pendulum, by measuring
the period of the roll, pitch and yaw motions. By rearranging the below equation, an
equation for the length of the pendulum can be found as a function of period [31].
2
2
∗
2
This period, however, is a damped period. To find the correct position of the
center of mass, the un-damped natural frequency must be used. To find this natural
frequency, the formula below is used, where ζ is the damping ratio.
1
ζ
The fact that the damped response observed in this experiment is a logarithmic
decrement helps define the damping coefficient. For a logarithmic decrement, the value
of
below can be found using the results measured by the IMU.
1
ζ
1
1
2
∗ ln
68
Wheere
data.
is foun
nd by comp
paring the am
mplitudes off two peaks measured iin the
is th
he larger of the two amp
plitudes and
is the sm
maller amplittude. The vaalue
is the numb
ber of period
ds separating
g the two am
mplitudes. In the below pplot of roll vversus
time in the pendulum experiment.
,
andd
are show
wn. This caalculation caan be
found in its entirety in Appendix
A
2.
Figure 27 - Roll
R Responsee in Pendulum
m Test
ng ratio is known, the orriginal equaation can be used to relatte the
Once the dampin
d
freq
quency, to the
t un-dampped natural frequency. This un-dam
mped
measured, damped
natural frequ
uency is then
n used to fin
nd the lengthh of the penddulum. Subtrracting the leength
of the pendu
ulum from th
he known diistance from
m the top of tthe vehicle to the pivot oof the
pendulum gives
g
the disstance from the top of the vehiclee to the centter of mass.. The
length of thee pendulum was found to
t be 4.23 [m
m]. Subtractiing the 3.31 [m] of penddulum
length meassured from the
t top of th
he vehicle too the pivot, this gives tthat the centter of
669
mass is 0.92
2 [m] from the
t top of th
he vehicle. M
Measured froom the keel, or bottom oof the
tracks, as it is traditionaally expresseed, this givess a KG of 0.55024 [m]. Itt is suggestedd that
c
out again
a
if futurre work requuires the possition of the center of grravity
this test be carried
as any chan
nge in the general arrang
gements of thhe vehicle’s systems willl have an im
mpact
on the exactt location.
3.1.3
Dyn
namometer Testing
T
The electric mo
otors origin
nally installeed on the vehicle werre tested onn the
namometer allows
a
for a broad rangge of tests tto be perforrmed.
dynamometter. The dyn
Measuring RPM, curreent, voltage and torque are all posssible on thhe device annd its
software. After initial dy
ynamometerr testing of thhe motors, itt was found that both yielded
the same reesults, so latter tests werre only perfo
formed with one motor for simpliciity of
reporting.
The first test rellated torquee and currennt at constannt motor RPM
M. Becausee they
are electric motors, thee torque incrreases linearrly with currrent, and thee RPM incrreases
linearly witth voltage. This
T
linear relationship
r
between torrque and cuurrent at diffferent
motor RPM
Ms can be seen in the figu
ure below.
770
50
45
40
Current [amps]
35
30
260 RPM
520 RPM
780 RPM
1300 RPM
1560 RPM
1950 RPM
2200 RPM
25
20
15
10
5
0
0
0.5
1
1.5
2
Torque [N-m]
2.5
3
3.5
4
Figure 28 – Dynamometer Test Results: Current-Torque Relationship at Different RPMs
From these results, because of the linear relationship found between current and
torque (characteristic of electric motors), an linear equation was found which relates
any current to the corresponding torque output of the motor. This equation was used in
determining the motor torque output based on current data collected during testing by
the motor controllers. Using this equation, and measuring the current to the motors, the
torque produced by the motors is defined. Once this torque is known, the gearing table
provided in section 2.1 can be used to relate the motor torque output to the force on the
tracks. Once this relationship is determined, it is now possible to use the motor current
data and calculate the force on the tracks when the vehicle is operated. This procedure
can be found in the Matlab code section of the appendix. The relationship between
71
current and torque is given in the end of this section, and is used in code with relates
current to motor torque, and track force.
The next dynamometer tests used a predefined test in the dynamometer
software. This test ramped up the torque to a user specified maximum, and measured
the motor RPM. This test was performed five times and yielded nearly identical results
each time. The electric motors are rated at 900 Watts, and have a maximum RPM of
2,600. With these known values provided by the manufacturer, it is possible to predict
the torque output of the motors with the below equation.
5252 ∗
Using the given values, a torque of 3.28 [Nm] is calculated. This value can also
be seen in the above figure to be accurate, as the current peaks to the maximum rating
of 35 [Amps] at this calculated torque. This value is a safe operating torque provided by
the motor at full RPM, and not exceeding the rated current of the motors. It can be
assumed the motors can provide a higher torque both at lower RPMs as well as with an
increased current. Supplying a current above the rated value of 35 [Amps] will not
cause damage if these instances of high torque requirements do no last more than a few
seconds at a time. It was assumed for short dynamometer tests, which last less than
fifteen seconds, the rated current could be exceeded without damaging the motors. The
maximum applied torque was set to 8.13 [Nm] in the below test and this value was
never reached.
72
3000
Test 1
Test 2
Test 3
Test 4
Test 5
2500
RPM
2000
1500
1000
500
0
-1
0
1
2
3
4
Torque [N-m]
5
6
7
8
9
Figure 29 - Dynamometer Test Results: RPM-Torque Relationship
The above graph shows an increase in torque at lower RPMs, this can be
explained by the V=IR relationship. The cusp in the graph above shows the power limit
of the motor controller. At this point, the power limit is reached, and the motor
controller will adjust its current limit slowly to provide an adequate torque output seen
above. This is a characteristic found on many electric motor controllers.
The last dynamometer test was performed to define the torque output of the
motors, and the results are shown in the figure below. The torque output was related to
the current into the motors at different motor commands. This data was used to define
the torque required to move the vehicle by measuring the applied current during testing.
73
3
2.5
Torque [N-m]
2
Motor Command: 50
Motor Command: 70
Motor Command: 80
Motor Command: 90
Motor Command: 100
Motor Command: 120
Motor Command: 125
1.5
1
0.5
0
0
5
10
15
20
25
Current [amps]
30
35
40
45
50
Figure 30 - Dynamometer Test Results: Current Torque Relationship for Different Motor
Commands
Again, because of the characteristics of electric motors, it was predicted that this
would result in a linear relationship between current and torque. Because of this
linearity, different motor commands can be estimated without explicit testing of each, as
well as higher measured current readings. As described above, the linear relationship
makes it possible to define a relationship that can be used to relate current and the
torque output of the motors.
The formula used to relate the motor current measured to the force on the track
is shown below, and the Matlab code which converts test data to track force can be
found in the appendix.
2.4868 ∗
This formula was found by the linear relationship of motor current and output
torque. A curve was fit to the data from the dynamometer test results, and the slope of
74
this equatio
on was used to relate an
ny current too a torque ooutput of thhe electric m
motor.
Then, the gearing
g
tablle was used
d to relate tthe torque output of tthe motor too the
corresponding force on
n the track. Because thhis relationshhip is also llinear, due tto the
gearing setu
up of the driivetrain, thesse two relatiionships cann be used to define a forrmula
relating the torque on th
he track to th
he torque outtput of the m
motor. Dividding the torquue on
the tracks by
y the radius of the drive sprocket givve the force on the trackk, which is reelated
to the curren
nt input of th
he motors through the dyynamometerr results.
3.1.4
Max
ximum Inclin
ne and Appro
oach/Departture Angles
Defiining the maaximum incline the vehiicle can travverse, as well as the apprroach
and departure angles it is
i capable off traversing, are both impportant in lim
miting damaage to
the vehicle’’s hulls or drivetrain in
n testing. T
The approachh angle is tthe angle onn the
forward parrt of the vehiicle, and lim
mits the obstaacles the vehhicle is capaable of traverrsing.
The departu
ure angle is the
t angle made by the rrear of the ddrivetrain annd the skeg oof the
propeller. This
T
departurre angle is also the maaximum inline the vehiccle is capabble of
traversing before
b
the propeller
p
is dragged. Thhe approachh angle was measured tto be
twenty degrrees and thee departure angle and maximum ttraversable incline is eleven
degrees. These angles arre illustrated
d in figure 299.
775
2
Fig
gure 31 - Vehiccle Approach and Departurre Angles
Duriing autonom
mous system
m developmeent, these aangles can bbe used to limit
hazardous situations,
s
as the system
m can moniitor the pitcch angle of the vehicle as it
navigates, and
a avoid thee maximum angles foundd above. Thiis technique can only bee used
when drivin
ng on a level surface.
The maximum traversable
t
incline
i
was noted as ann unknown tthat needed to be
t CISD fo
or the autono
omous modeeling develoopment. Whiile this anglee was
defined by the
defined thro
ough testing,, the tests alsso aimed at ggiving future test develoopers inform
mation
on the poweer draw of th
he motors du
uring these ddemanding m
maneuvers. W
While the veehicle
may be ablee to traversee a steep inclline, the straain on the m
motors for ann extended pperiod
could causee damage. To
o understand
d this, the veehicle was ooperated on different incclines
to define the current draw by the motors.
m
The electric mottors are ratedd for 35 [Am
mps],
and while th
his value caan be exceed
ded for a shoort period oof time, a higgh current ffor an
extended peeriod will daamage the motors.
m
The angle the vvehicle is traaversing is eeasily
776
monitored by the onboard sensors, so both testing and autonomous navigation can
monitor this incline, and from the test results described below, damage can be avoided
by avoiding prolonged incline traversing.
The vehicle was tested on the beach on inclines of 11, 14 and 19 [deg]. During
the vehicle’s operation on these inclines, the current to the motors was measured and
recorded, along with IMU data, most importantly the pitch angle.
The vehicle was operated at an equal motor command of 100 to both port and
starboard motors for each test, the port and starboard motor current, force on the tracks
and IMU pitch angle are shown in the figures below.
It is important to note that a data collection error occurred so the motor data is
not synchronized with the IMU data (for these incline tests only). Therefore the motor
current and forces are plotted vs. time step rather than coordinated time as in other data
presentation.
Figures 31 and 32 show the pitch angle, which is the angle the vehicle is
traversing. The vehicle was started at the base of the incline and stopped immediately
77
Port [Amps]
20
40
60
80
100
120
100
50
0
0
20
40
60
80
100
120
1000
500
0
0
20
40
60
80
100
120
1000
500
0
0
20
40
60
Time Step
80
100
120
Figure 32 - Motor Data 11 Degree Incline Test
16
14
12
Pitch Angle [deg]
Stbd Force [N] Port Force [N]
100
50
0
0
Stbd [Amps]
after the incline, so the motor data is when the vehicle is operating on this incline.
10
8
6
4
2
40
50
60
70
80
Time [sec]
Figure 33 - Pitch Angle 11 Degree Incline Test
78
90
100
110
Table 7 gives the average values found in this test while operating the vehicle up
an 11 degree incline. It was found that the average current was just above the rated
motor current. This means the vehicle is able to traverse an 11 degree inline safely for a
period of time without causing severe strain on the electric motors. The force on the
tracks during this incline test was found to be significantly larger than the force on the
tracks during the beach transition results, shown later in this section. The average value
of the beach transition tests was 183.68 [N], where it was found here to be 317.73 [N],
about 58% larger.
Table 7 - Average Current and Track Force in 11 Degree Incline Test
Average Current Port [Amps]
Average Current Stbd [Amps]
Average Force Port [N]
Average Force Stbd [N]
35.36
42.53
288.47
347.00
The next incline test was performed on a 14 degree incline. Again, the motor
controller data was recorded without a UTC timestamp, so it will not be plotted versus
time in the below graphs.
79
Port [Amps]
20
40
60
80
100
120
140
Stbd [Amps]
100
50
0
0
20
40
60
80
100
120
140
1000
500
0
0
20
40
60
80
100
120
140
1000
500
0
0
20
40
60
80
100
120
140
Time Step
Figure 34 - Motor Data 14 Degree Incline Test
18
16
14
12
Pitch Angle [deg]
Stbd Force [N] Port Force [N]
100
50
0
0
10
8
6
4
2
0
-2
30
40
50
60
Time [sec]
70
Figure 35 - Pitch Angle 14 Degree Incline Test
80
80
90
The average value of the beach transition tests was 183.68 [N], where it was
found here to be 339.34 [N], about 85% larger. This test showed an average force
roughly 6% larger than the 11 degree incline.
Table 8 - Average Current and Track Force in 14 Degree Incline Test
Average Current Port [Amps]
Average Current Stbd [Amps]
Average Force Port [N]
Average Force Stbd [N]
39.49
43.69
322.17
356.50
The final incline test was performed on a 19 degree incline. This test showed the
operating limits of the vehicle. The vehicle was unable to traverse this incline, both
because of power and physical limitations. The vehicle was unable to keep forward
momentum during the test up the incline with motor commands of 100. Although it may
have been possible to execute the test with full power to both motors, physical
limitations on this steep incline were found to hold back the vehicle. The rear of the
vehicle, specifically the bottom of the propellers, came into contact with the flat sand
when the vehicle was inclined in this test. Therefore this was found to be the limit on
the traversable slope of the vehicle. Below is the motor data and pitch angle of the
vehicle. In this test, the motor data was collected synchronized with the IMU data, so
the X axis timescales are the same, and the data is shown below.
81
Port [amps]
25
30
35
40
45
50
55
Stbd [amps]
200
100
0
20
25
30
35
40
45
50
55
1000
500
0
20
25
30
35
40
45
50
55
1000
500
0
20
25
30
35
40
45
50
55
45
50
55
Time [sec]
Figure 36 – Motor Data 19 Degree Incline Test
25
20
Pitch Angle [deg]
Stbd Force [N] Port Force [N]
200
100
0
20
15
10
5
20
25
30
35
40
Time [sec]
Figure 37 - Pitch Angle 19 Degree Incline
82
The current draaw measured in this teest were 666% larger thhan the rateed 35
[Amps] of the motors.. If the veh
hicle was suubjected to an incline tthis steep fo
for an
mage would ooccur.
extended peeriod of timee, motor dam
Table 9 – Av
verage Curren
nt and Track Force in 19 D
Degree Incline Test
Average
e Current Port [Amps]
Average
e Current Stb
bd [Amps]
Average
e Force Port [N]
Average
e Force Stbd [N]
54.83
61.46
447.39
501.45
The results of these
t
tests show
s
that thhe vehicle sshould not bbe operated over
1 degrees for
f extended
d periods, ass the high cuurrent could cause damaage to
inclines of 10
the electric motors.
m
Testting conditio
ons should bbe limited to this value w
whenever posssible
so vehicle damage willl not occur. Additionallly, inclines over 15 deegrees should be
avoided at all
a times, as physical daamage can ooccur to the vehicle’s prropellers or other
parts of the vehicle hull.
Thiss information
n should be taken into aaccount whenn choosing a test area foor the
vehicle, and
d the autonom
mous system
m should be designed too monitor thiis slope usinng the
IMU to avoid prolonged
d operation on
o inclines oover 10 degreees.
3.1.5
Land
d Maneuveriing Characteeristics
Miniimum turnin
ng radius: Th
he minimum
m turning raddius was onee of the variiables
reported as an unknow
wn that needed to be ddetermined for further development of
autonomouss algorithms by the CISD. To determ
rmine this vaalue, the ressults of the m
motor
command teests (describ
bed below) were used. The tightesst turn the vvehicle is abble to
make whilee keeping bo
oth tracks in
n motion is 100% poweer on one trrack and rouughly
883
30% on thee other. Any
y command lower than these causeed undesirabble results aas the
vehicle wou
uld drag onee track and cause
c
a sidew
ways sand-pplowing effeect with its iinside
track. This safe operatin
ng turn is a motor comm
mand combination of 125 on one m
motor
and 45 on th
he other, an
nd provides a very tight turn in bothh directions. Figure 37 sshows
this turn in both the rig
ght and left directions.
d
Itt should be m
mentioned thhat the vehicle is
capable of sharper
s
turns than this, and can eveen pivot by putting one track in forrward
and one in reverse. Ho
owever, thesse maneuverrs should bee used for ooccasions such as
v
is in close pro
oximity to an obstaclee, and not uused for noormal
when the vehicle
navigation. The strain these
t
maneu
uvers put on the vehicle’s drivetrainn make them
m best
used only when
w
required
d. The turnin
ng radius wiith motor com
mmands of 125 and 45 rresult
in a fairly tiight turn wh
hile keeping forward mom
mentum. Thhis should bee the tightestt turn
the vehicle needs
n
to exeecute most of
o the time, rreserving thee extreme tuurns for situaations
that absolutely require them.
t
As sho
own below, the 125 andd 45 motor coommands giives a
ughly one veehicle lengthh.
turning radius that is rou
Figure
F
38 - Miinimum Turn
ning Radius on
n Land
884
To find
f
the diaameter of th
he circle coompleted byy the vehiclle, the dataa was
condensed to
t only the middle circlle, as shownn below. Thhis procedurre can be seeen in
attached Maatlab code (A
Appendix 2),, and shown in figure 388.
Figure 39
9 - Clipped Da
ata to Calculatte Minimum T
Turning Radiu
us
f
the diam
meter of thiis circle, thee maximum and minimuum latitude were
To find
found, as well
w as the maximum
m
and
d minimum longitude. T
These four ppoints corresspond
to the northeern-most, so
outhern-mostt, eastern-moost and westtern-most pooints of the ccircle.
Then the Haversine
H
forrmula was used
u
to find the distancce between tthese points. The
Haversine formula
f
is ussed to find th
he distance bbetween poinnts on a sphhere. By usinng the
radius of th
he earth, one can use this formuula to find the distancce between GPS
coordinates..
By finding the distance beetween the maximum aand minimuum latitudess, the
vertical, or north-to-sou
n
uth diameter is found. Sim
milarly, findding the distance betweeen the
885
maximum and minimum longitudes gives the horizontal, or east-to-west diameter.
These values, as well as the coordinate points used in the calculations, are shown in
Tables 10 and 11 below.
For a right turn at motor commands of 125 port, 45 starboard, a turning radius of
2.4 [m] was found.
Table 10 – Coordinates for Minimum Right Turning Radius Calculations
Maximum/Minimum Latitude Points Northern‐most [decimal coordinates]
Southern‐most [decimal coordinates]
Distance Between Points [m]
Latitude
Longitude 26.05514067 ‐80.11260933
26.05502201 ‐80.11258117
4.9
Maximum/Minimum Longitude Points Eastern‐most [decimal coordinates]
Western‐most [decimal coordinates]
Distance Between Points [m]
Latitude
Longitude 26.05503883 ‐80.11233983
26.05514051 ‐80.11261033
4.7
Similarly, for a left turn at motor commands of 45 port, 125 starboard, a turning
radius of 3.73 [m] was found. Which gives an average turning radius 3.06 [m].
Table 11 - Coordinates for Minimum Left Turning Radius Calculations
Maximum/Minimum Latitude Points Northern‐most [decimal coordinates]
Southern‐most [decimal coordinates]
Distance Between Points [m]
Latitude
Longitude 26.05508451 ‐80.11257783
26.05501817 ‐80.11258217
7.4
Maximum/Minimum Longitude Points Eastern‐most [decimal coordinates]
Western‐most [decimal coordinates]
Distance Between Points [m]
Latitude
Longitude 26.05505033 ‐80.11254533
26.05504817 ‐80.11262033
7.5
Maximum Velocity and Acceleration: The maximum velocity and accelerations
were found by starting the motors at the maximum value at time zero. The vehicle was
operated until it reached maximum velocity and then the motors were set to zero. This
test gave GPS data that could be used to find maximum acceleration, maximum velocity
and the vehicles deceleration. The vehicle has an average maximum velocity of about 2
[m/s], and its acceleration is about 1 [m/s2], which means it takes two seconds to obtain
top speed velocity. When stopping, the vehicle came to a skidding stop in the sand.
Without this observed slipping, this deceleration is expected to be lower.
86
Table 12 - Maximum Velocity and Accelerations on Land
Acceleration 1
Acceleration 2
Acceleration 3
Acceleration 4
Average Accel
[m/s^2]
[m/s^2]
1.00 Deceleration 1
1.33 Max Velocity 1
0.93 Deceleration 2
0.79 Max Velocity 2
0.96 Deceleration 3
1.73 Max Velocity 3
0.83 Deceleration 4
0.83 Max Velocity 4
0.93 Average Decel
1.17 Average Max Vel
[m/s
2.03
1.89
1.96
1.76
1.91
Figures 39-41 show the GPS velocity, as well as motor information for the
maximum velocity tests. It can be seen at the start time the current to the motors is at a
maximum and the velocity begins to increase, until it levels off at its maximum around
2 [m/s]. The increased current during initial acceleration shows the high motor torque
required to move the vehicle from rest. All measurements were coordinated through
UTC time in seconds. Because the results of all the maximum speed tests provided
similar results, as seen in the above table, only one case is illustrated in the figures
below.
87
2.5
Velocity [m/s]
2
1.5
1
0.5
0
13
13.5
14
14.5
15
15.5
Time [sec]
16
16.5
17
17.5
18
Figure 40 - Maximum Velocity on Land
120
Port Current
Starboard Current
100
Current [amps]
80
60
40
20
0
0
0.5
1
1.5
2
2.5
UTC Time [sec]
3
3.5
Figure 41 - Maximum Velocity Motor Current
88
4
4.5
5
128
127.8
Starboard Motor Command
Port Motor Command
127.6
Motor Command
127.4
127.2
127
126.8
126.6
126.4
126.2
126
0
0.5
1
1.5
2
2.5
UTC Time [sec]
3
3.5
4
4.5
5
Figure 42 - Maximum Velocity Motor Commands
Course Keeping-ability and Motor Control Compensation: During maximum
velocity tests, it was found the vehicle did not track a straight line when both motors
were given full power command. The vehicle tracks slightly to the left when both
motors are given the same command. The rate of this left tracking was just about five
degrees per second, which is significant over any extended straight line track. It would
only take about 30 seconds to become 180 degrees off track.
It was concluded this leftward track is a result of the drivetrain not being
symmetric in the amount of torque to move the track. Because it takes slightly more
torque to drive the right track, the current is higher on this motor, as seen in the motor
current plot above. During dynamometer testing, it was found that the motor controllers
compensate for this by increasing the voltage to the motor slightly. This can be seen in
the dynamometer test results where the torque is plotted versus RPM. The elbow in the
89
graph is the power limit of the motor controller, and it will increase voltage slightly as
the current increases. This will be explained in more detail in the dynamometer results
section, but is the cause for the non-linear increase in yaw rate seen in this test.
Below are the results of equal full speed motor commands to both land motors.
The same left track was also observed in lower motor commands. The GPS rate of turn
plots below show the leftward track of just under 5 [deg/sec] average for the four tests.
0
-0.5
-1
Yaw Rate [deg/sec]
-1.5
-2
-2.5
-3
-3.5
-4
-4.5
-5
0
2
4
6
8
10
Time [sec]
12
14
Figure 43 - Rate of Turn During Maximum Speed (Test 1)
90
16
18
20
0.5
0
-0.5
Rate [deg/sec]
-1
-1.5
-2
-2.5
-3
-3.5
-4
-4.5
0
5
10
15
20
25
20
25
Time [sec]
Figure 44 - Rate of Turn During Maximum Speed (Test 2)
1
0
Rate [deg/sec]
-1
-2
-3
-4
-5
-6
0
5
10
15
Time [sec]
Figure 45 - Rate of Turn During Maximum Speed (Test 3)
91
0
-0.5
-1
Rate [deg/sec]
-1.5
-2
-2.5
-3
-3.5
-4
-4.5
-5
0
5
10
15
20
25
Time [sec]
Figure 46 - Rate of Turn During Maximum Speed (Test 4)
The IMU was also used in these tests to understand the yaw rate expereienced
during equal motor commands. The figure below shows the measured yaw rate for one
of the max speed tests. Again, as with the GPS data, this data shows a 5 [deg/sec]
tracking error when the vehicle is given equal motor commands.
92
6
4
IMU Yaw Rate [deg/sec]
2
0
-2
-4
-6
-8
-10
0
5
10
15
Time [sec]
20
25
30
Figure 47 - IMU Yaw Rate for Equal Motor Commands
This leftward track can also be seen in the compass data during the maximum
speed tests. As seen below, the vehicle’s heading changes significantly over the course
of the test.
93
145
140
Heading [deg]
135
130
125
120
115
110
0
2
4
6
Time [sec]
8
10
12
Figure 48 - Maximum Speed Compass Heading (Test 1)
145
140
Heading [deg]
135
130
125
120
115
22
23
24
25
26
27
Time [sec]
28
29
Figure 49 - Maximum Speed Compass Heading (Test 2)
94
30
31
32
145
140
Heading [deg]
135
130
125
120
115
11
12
13
14
15
16
Time [sec]
17
18
19
20
21
Figure 50 - Maximum Speed Compass Heading (Test 3)
140
135
Heading [deg]
130
125
120
115
110
12
14
16
18
Time [sec]
20
Figure 51 - Maximum Speed Compass Heading (Test 4)
95
22
24
By looking at the third figure above of the vehicle compass data for example, it
can be seen that the heading changes from 144 degrees at time zero, to about 120
degrees after five seconds. This is a rate of turn of just under 5 [deg/sec].
To compensate for this straight line tracking error, a correction factor was found
to add to the left motor. This would allow the vehicle to track a straight line even if
motors were set at equal commands. This information will be crucial in autonomous
navigation development because it will correct the vehicle from traveling off course
when the system would like to track a straight line.
After experiments, this correction factor was found to be a difference in motor
commands of 10. For example, giving a motor command of 60 to port and 50 to
starboard resulted in a straight tracking vehicle. This correction must be used in
autonomous navigation to allow the vehicle to track a straight line. This factor was also
added into zig-zag maneuvering tests to give equal turns to both port and starboard.
This will be described in the maneuvering section. The picture below shows the tracks
in the sand after the vehicle has driven a straight line, and the tracks are traced with two
red lines.
96
Figure 52 - Straigh
ht Line Track
k with Correcttion Factor
Thiss correction factor
f
is imp
portant for auutonomous ccontrol deveelopment beccause
it is necessaary for the veehicle to tracck a straight line when ggiven equal m
motor comm
mands.
If this correection is not factored intto control, thhe autonomoous control system will have
to constantly
y correct forr a leftward tracking
t
vehhicle.
Moto
or Command
d Testing:
The results prov
vided here from
f
the mootor commannd testing w
will be usefuul for
autonomouss developmeent becausee it defines the input-ooutput relattionship bettween
motor comm
mands and the
t resulting
g response oof the vehiclle. These tests provide more
997
information than a traditional turning circle test, which reveals characteristics of a
vehicle, but does not give the wide range of values that these tests have provided.
A range of motor commands were used to define the vehicle’s motion response.
Values from a slight turn, to the tightest turn the vehicle is capable of were used, and
the vehicles IMU, compass, GPS and motor controllers were used to measure the result
of these commands.
To simplify the presentation of the data found. Many of the results found in this
section will be displayed in a table, and plots of the data can be found in the appendix.
Each test resulted in over 10 graphs from all the sensors, therefore only a specific
selection will be presented in the main text.
Turning radius: The first value that was defined in these tests is the resulting
turning radius for a particular motor input. The radius was found using the Haversine
formula method, which was described in detail in the minimum turning radius section
above. Below is a table of the resulting turning radii for each motor command
combination. The values are listed in largest to smallest. The value was found by taking
the average of the vertical and horizontal radii.
Table 13 – Land Left Turn Radii
Motor Command Port
75
35
45
45
55
35
45
55
Motor Command Starboard
105
55
125
75
105
75
105
125
98
Turning Radius [m]
5.34
5.24
3.72
3.69
2.44
2.21
1.97
1.93
Table 14 – Land Right Turn Radii
Motor Command Port
55
75
75
105
105
125
Motor Command Starboard
35
45
35
55
45
45
Turning Radius [m]
9.92
5.57
4.15
4.06
2.93
2.24
Yaw rate: The next set of important data that was found from the motor
command tests was the resulting yaw rate of each virtual rudder motor input. The yaw
rate was found by averaging the yaw rate measured over the course of the vehicle turn,
while the virtual rudder was deflected. This yaw rate is one of the outputs of vehicle
rudder and velocity inputs, and is useful when developing the vehicle’s autonomous
control system, to understand the output of motor command inputs.
A turning circle test causes the vehicle to turn at a constant rate until the rudder
is returned to zero, or no deflection. Below is an example of the yaw rate measured
during a turning circle test on land. A negative yaw rate means a left turn, or a counter
clockwise rotation.
99
2
0
GPS Rate of Turn [deg/sec]
-2
-4
-6
-8
-10
-12
-14
-16
0
20
40
60
80
100
120
140
Time [sec]
Figure 53 - Yaw Rate During a Turn to Port
The slight instability of yaw rate during the circle test shown above is mainly
caused by the inconsistency of the sandy ground in the test area. Because the ground is
not perfectly flat or smooth, the rate varies slightly during the turn. It can be seen when
the vehicle is at rest both before and after the turn that this fluctuation is not due to
sensor noise, as the rate is constant when the vehicle is not moving. Performing the test
on a paved surface such as a parking lot would most likely yield a more constant yaw
rate; however this vehicle will primarily operate on a beach, so these tests were
performed on flat sand.
Below is a table showing the average yaw rates found for each test. The average
and variance were found during the time the vehicle’s virtual rudder was deflected.
100
Table 15 - Land Left Turn Yaw Rate
Motor Command Port
55
45
55
35
75
45
45
105
35
Motor Command Starboard
125
105
105
75
105
125
75
125
55
Yaw Rate [deg/sec]
‐35.99
‐24.58
‐22.08
‐14.11
‐12.72
‐9.66
‐9.66
‐7.35
‐4.84
Variance [deg^2/sec^2]
4.8532
1.9633
1.0792
1.7432
0.5256
1.9633
1.1044
0.3914
0.4955
Table 16 - Land Right Turn Yaw Rate
Motor Command Port
125
105
105
75
125
75
105
55
Motor Command Starboard
45
45
55
35
105
45
75
35
Yaw Rate [deg/sec]
27.55
17.67
14.61
8.66
7.41
7.35
6.42
2.77
Variance [deg^2/sec^2]
3.2299
2.9037
0.8924
1.3763
0.3875
0.6661
0.1981
0.1948
Motor Current: The motor current was measured during the tests, which can be
correlated to the force on the tracks during the turning circle maneuver. While a
complete set of data is available in Appendix 1 for each of these tests, it is worth
comparing this motor controller data for two separate tests to show the amount of force
on the tracks and current demand from the motors in these maneuvers. It is expected, as
seen in Figures 53 and 54, that the tighter turn demands more from the outside motor, in
the case of a left turn, the starboard motor. The axis scales were held constant for both
plots so it is easy to compare the two tests. The 105/45 tighter turn shown second,
requires a track force of over 400 [N] for almost the entire test. On the other hand, the
105/75, less sharp turn stays below 400 [N] for almost the entire test. The average force
on the starboard track is 254.58 [N] for the wide turn of 105/75 and 475.72 [N] for the
101
tighter turn, which is almost double the required track force. Because of the linearity of
the drivetrain forces, seen in the dynamometer results Section 3.1.1.2, this results in
Force on Track [N]
almost double the required torque output from the motor.
800
Starboard
Port
600
400
200
0
0
5
10
15
20
25
30
35
40
45
50
Current [Amps]
150
Starboard
Port
100
50
0
0
5
10
15
20
25
30
Time [seconds]
35
40
45
50
Force on Track [N]
Figure 54 - 105/75 Left Turn Current and Force on Tracks
800
Starboard Motor
Port Motor
600
400
200
0
0
5
10
15
20
25
30
35
40
45
Current [amps]
150
Starboard Motor
Port Motor
100
50
0
0
5
10
15
20
25
Time [seconds]
30
Figure 55 - 105/45 Left Turn Current and Force on Tracks
102
35
40
45
It is important to note here the current draw during the two tests. The first test
shown above, which is the wider of the two turns, shows the current during the turn
stays below 50 [Amps] the entire test. However, the tighter turn, of 105/45, stays above
50 [Amps] for a majority of the test. The averages are 31.20 [Amps] and 58.31 [Amps]
for the wide and tight turns, respectively.
Drivetrain requirements become larger as the vehicle makes sharper turns. The
motor torque is linearly related to the current, and as the turns become sharper, the
current to the motors increases. This must be taken into account as the motors can be
damaged if the rated power is exceeded for an extended period of time.
Vehicle Heading: The vehicle’s heading was also measured during these tests
by the OS5000 compass. Below is an example of the vehicle’s heading during a right
turn on land, with motor commands of 75 port and 35 starboard. As shown above, the
yaw rate, or vehicle’s rate of turn, stays fairly constant throughout the test. The figure
below also shows this to be true in the compass data as well.
103
400
350
Heading [deg]
300
250
200
150
100
50
0
0
50
100
150
Time [sec]
Figure 56 - Vehicle Heading During a Land Right Turn
This data can be modified by adding 360 degrees to the data when it crosses due
north, or zero degrees. This helps show the constant yaw rate of the vehicle during the
turn as seen in the yaw rate section above. Again, as in the yaw rate data recorded from
the GPS, the compass heading data shows some inconsistency during the turn. This is
due to the test area ground, and because the compass was properly calibrated, not
because of sensor noise. This can be seen when the vehicle is at rest and the heading is
perfectly constant.
104
800
700
Adjusted Heading [deg]
600
500
400
300
200
100
0
0
20
40
60
80
100
120
140
Time [sec]
Figure 57 - Continuous Compass Data During Land Right Turn
Zig-Zag Test: The zig-zag test is a traditional test used in maneuvering
experiments. It is especially useful for system identification, and fitting an equation to
the data set. The zig-zag test was performed in the same sand area as the turning circle
tests. The tests were performed open loop, with five combinations of motor commands,
and used the entire test area.
The motor commands used in the zig-zag tests are shown in the table below.
Each test was performed two times in case of errors with data collection. A complete set
of results can be seen in the appendix.
105
Table 17 - Land Zig-zag Test Motor Commands
Yaw Rate [deg/sec]
Motor 1 Motor 2
70
40
110
70
110
80
122
80
122
100
20
10
0
-10
-20
60
65
70
75
80
85
90
95
100
105
85
90
95
100
105
85
90
95
100
105
Port Command
Time [sec]
80
60
40
20
0
60
65
70
75
80
Stbd Command
Time [sec]
80
60
40
20
0
60
65
70
75
80
Time [sec]
Figure 58 - 70/40 Land Zig-zag Test
The zig-zag test results are useful for the systems identification method
described in the experimental approach section. Having the motor inputs, and
measuring the IMU yaw rate can be used to estimate a simple integral controller, and by
using the X and Y velocities measured, the data can be used to estimate a more complex
model for autonomous control. Systems identification results will be described in
3.1.1.7.
106
3.1.6
Sea Maneuverin
ng Characteriistics
The vehicle wass tested in a part of the Intracoastall Waterway in Dania B
Beach,
FL. This areea is sheltereed from win
nd and has m
minimal boatt traffic to aaffect testingg. The
vehicle only
y experienceed minor wind produceed waves, annd can be sseen in figurre 59
below.
Figure 59 - Final
F
Vehicle iin Water Test Area
Miniimum turnin
ng radius: The minimum
m turning raddius in wateer navigationn was
found using
g the Haversine formulaa procedure described inn the land tuurning radiuus test
in Section 3.1.1.5.
3
For water navig
gation, the m
minimum turrning radiuss was foundd with
100% forwaard on the starboard
s
mo
otor and 1000% reverse on the port motor, or m
motor
commands of
o 125 and -125,
respecctively, whicch results in a turn as shhown in figuure 58
below.
1007
Figure 60 - Minimum
M
Turin
ng Radius in W
Water
Thiss maneuver resulted
r
in a turning radiius of 1.93 [m
m]. The GPS
S locations oof the
maximum and
a
minimu
um points used
u
in the Haversine calculation,, as well aas the
distance bettween these points
p
is sho
own in table 18 below.
Ta
able 18 – Coorrdinates for Minimum
M
In-W
Water Turningg Radius Calcculations
Maxim
mum/Minimum Latittude Points Northern
n‐most [decimal coordin
nates]
Southern
n‐most [decimal coordin
nates]
Distancee Between Points [m]
Latitude
Longitude 26.016387 ‐80.12286417
7
26.016339 ‐80.12287683
3
5.5
Maximum/Minimum Longitude Pointts Eastern‐most [decimal coordinates]
Western‐most [decima
al coordinates]
Distance Between Poin
nts [m]
Latitude
L
Longitude 26.01635967 ‐80.1228535
‐
26.01636017 ‐8
80.12289967
4.6
Maxximum Veloccity and Accceleration: T
The maximum
m velocity aand acceleraations
were found by starting the propeller motors at the maxim
mum value aat time zero. The
vehicle was operated un
ntil it reached maximum
m velocity annd then the m
motors were set to
zero. This gave
g
GPS daata that coulld be used too find maxim
mum accelerration, maxiimum
velocity and
d the vehiclees deceleratio
on. The vehiicle has an aaverage maximum velocity of
1.19 [m/s], and its accceleration is 1.98 [m//s2]. The plots of veloocity and m
motor
n can be seeen below. The
T current to the mottors is seen to be relattively
information
1008
constant throughout the test, except for the drop in the starboard current about half way
through the test. This seems to be an error in sensor data transmission because the
velocity stays constant during this one second drop in current. This was considered a
motor controller data logging error and did not affect the test. The time-scales for all
plots below are constant, and it can be seen at the start time of the test, the motors are
set to the maximum value and the velocity begins to increase until it reaches a
maximum just under 1.2 [m/s]. The table below summarizes the maximum values found
in this test.
Table 19 - Maximum Velocity and Acceleration in Water
Maximum Velocity
1.19 [m/s]
Maaximum Acceleration 1.98 [m/s^2]
1.4
1.2
Velocity [m/s]
1
0.8
0.6
0.4
0.2
0
0
5
10
15
20
Time [sec]
25
Figure 61 - Maximum Velocity Water
109
30
35
40
40
Starboard
Port
35
Current [Amps]
30
25
20
15
10
5
0
0
5
10
15
20
Time [sec]
25
30
35
40
Figure 62 - Motor Current During Maximum Velocity Test Water
126
Starboard
Port
125.8
125.6
Motor Command
125.4
125.2
125
124.8
124.6
124.4
124.2
124
0
5
10
15
20
Time [sec]
25
30
35
40
Figure 63 - Motor Commands During Maximum Velocity Test Water
Course Keeping-ability and Motor Control Compensation: As in land testing,
water tests also showed the vehicle was unable to track a perfectly straight course. In
110
this situation, the cause is not the torque required to move the drivetrain as it was in
land testing. This instability is caused by a phenomenon called “propeller walk.”
Because the propellers both spin in the same direction (counter-clockwise), they cause a
force on the rear of the vehicle to the port side. This causes a slight starboard turn,
which keeps the vehicle from keeping its course. Below in Figure 64 a plot in Google
Earth of the vehicle’s position, and the compass heading during its course, which was
adjusted by adding 360 degrees to show a continuous plot. As seen in Table 20, the
wind was actually opposing the rightward track, as it was coming out of the southwest,
and that is the direction in which the vehicle is tracking. So it is clear that this track in
not related to wind.
Table 20 - Wind Data During Straight Line/Max Speed Tests
Direction SW
SW
SW
SW
Wind Speed [m/s]
3.00
2.82
3.08
2.59
111
Test
MC=40
MC=80
MC=100
MC=125
Figure 64 - Straight Linee Track in Waater
360
0
340
0
320
0
Heading [deg]
300
0
280
0
260
0
240
0
220
0
200
0
180
0
0
2
4
6
8
10
Time [sec]
T
12
14
Figure 65 - Comp
pass Heading During Straigght Track
1 12
16
18
20
By looking at the GPS and IMU’s yaw rate data as was done during the land
tests, it can be seen that the IMU gives an average yaw rate of about 8 [deg/sec] and the
GPS gives a similar result.
IMU Yaw Rate [deg/sec]
10
5
0
-5
-10
80
85
90
95
100
105
Time [sec]
110
115
120
125
130
115
120
125
130
Figure 66 - IMU Yaw Rate Full Speed Water
12
GPS Rate of Turn [deg/sec]
10
8
6
4
2
0
-2
-4
80
85
90
95
100
105
Time [sec]
110
Figure 67 - GPS Yaw Rate Full Speed Water
113
It was found a correction factor of 5 was able to compensate for this propeller
walk and the vehicle tracks a straight course with this correction factor added to the
code. This correction factor is important to consider in the autonomous control system
of the vehicle, as it will be easier to control a vehicle that is able to keep a straight
course when given equal motor commands, which correlates to a virtual rudder
deflection of zero.
Motor Command Testing:
The water motor command tests were carried out in the same way as described
in the land motor controller tests. The input-output relationship between motor
commands and vehicle response was defined through these tests, and they covered more
input rudder commands than a standard turning circle test, as described by ABS in [39].
The motor commands used were chosen to produce turns that would be expected
in autonomous navigation, and large radius turns were not performed because they were
deemed unnecessary, the largest radius tested was 12 [m]. As in land tests, the GPS,
IMU, compass and motor controllers were used to collect data during the tests. Unlike
the land tests, however, the wind speed and direction were recorded during these tests
because this could affect the turning path of the vehicle.
The data from these tests will also be presented here in tables for space
consideration. A full documentation of data is included in Appendix 1. Only a selection
of data will be displayed in the main text for discussion purposes.
114
Wind Speed and Direction
Below are tables of the wind speed measured during the water turning circle
tests. The wind speed is the average wind speed at the beginning of each test.
Table 21 – Wind Data During Left Turn Tests
Direction
SW
SW
SW
SW
SW
SW
SW
SW
SW
SW
SW
WSW,SW
Wind Speed [m/s]
3.40
3.62
3.49
3.49
2.91
3.98
3.31
2.91
3.62
3.31
3.00
3.00
Test
80,‐40
80,‐80
80,0
100,0
100,‐40
100,‐80
100,‐100
125,0
125,45
125,‐45
125,‐85
125,‐125
Table 22 - Wind Data During Right Turn Test
Direction WSW
SW
SW
SW
SW
SW
SW
SW
SW
SW
SW
Wind Speed [m/s]
3.31
3.40
3.31
2.91
2.01
3.22
2.91
2.50
2.50
2.59
3.40
115
Test
80,‐40
80,‐80
100,0
100,‐40
100,‐40
100,‐80
100,‐100
125,0
125,‐45
125,‐85
125,‐125
Turning radius: The first value that was defined in these tests is the resulting
turning radius for a particular motor input. The radius was found using the Haversine
formula method, which was described in detail in the minimum turning radius section
above. Below is a table of the resulting turning radii for each motor command
combination. The values are listed in largest to smallest radius. The value was found by
finding the average of the vertical and horizontal radius.
Table 23 - Water Left Turning Radii
Motor Command Port Motor Command Starboard Turning Radius [m]
0
100
11.75
0
125
11.05
0
80
10.85
‐40
100
8.62
‐45
125
7.81
‐80
100
5.28
‐100
100
3.13
‐125
125
2.52
Table 24 - Water Right Turing Radii
Motor Command Port Motor Command Starboard Turning Radius [m]
125
0
9.15
100
0
8.96
125
‐45
7.84
100
‐40
7.54
125
‐85
7.12
80
‐40
6.88
100
‐80
6.62
80
‐80
5.04
100
‐100
4.70
125
‐125
4.52
What was found in these turning radius tests is that the tightest turns are
executed when one motor is forward and one is in reverse. Because the vehicle’s
116
drivetrain is not retractable, it sticks out under the hulls and acts like a keel, which helps
with straight line tracking, but negatively affects the vehicle’s turning radius. Looking
at the lower turning radii shown in the tables above, the larger the reverse motor, the
smaller the turning radius.
While it was not tested, because the thrust in the forward direction is much
larger than when in reverse, an even smaller turning radius is assumed to be achieved by
giving full reverse command to one motor and half forward command to the other
motor. This would result in an even tighter radius, and could even cause the vehicle to
spin on its axis.
Yaw rate: The next data found from these tests is the resulting turning radius
from each motor command. As stated above, this data will be presented in a table, and
plots of the data is provided in the appendix.
Table 25- Water Left Turn Yaw Rate
Motor Command Port
‐125
‐100
‐80
‐45
0
‐40
0
0
Motor Command Starboard Average Yaw Rate in Turn [deg/sec]
125
‐9.29
100
‐7.69
100
‐5.66
125
‐4.90
125
‐3.80
100
‐3.62
100
‐3.20
80
‐2.66
117
Varience [deg^2/sec^2]
0.8395
0.7987
0.3174
0.3687
0.3892
0.8510
0.4418
0.8151
Table 26 - Water Right Turn Yaw Rate
Motor Command Port
125
100
125
125
80
125
100
100
100
80
Motor Command Starboard
‐125
‐100
‐85
‐45
‐80
0
‐80
‐40
0
‐40
Yaw Rate [deg/sec]
8.05
7.01
6.34
6.08
5.82
5.74
5.73
5.62
4.91
4.75
Varience [deg^2/sec^2]
0.1179
0.1003
0.1411
0.1080
0.3648
0.0790
0.2673
0.0509
0.1334
0.1344
The yaw rate was found by averaging the yaw rate measured over the course of
the vehicle turn, while the virtual rudder was deflected. This yaw rate is the output of
the vehicle rudder input and velocity, and is useful when developing the vehicle’s
autonomous control system, to understand the output of motor command inputs.
A turning circle test causes the vehicle to turn at a constant rate until the rudder
is returned to zero, or no deflection. Below is an example of the yaw rate measured
during a turning circle test in the water. A negative yaw rate means a left turn, or a
counter clockwise rotation.
118
2
1
GPS Yaw Rate [deg/sec]
0
-1
-2
-3
-4
-5
-6
-7
0
20
40
60
80
100
Time [sec]
120
140
160
180
200
Figure 68 – Yaw Rate During a Turn to Port (100 Stbd, -80 Port)
Maneuvering Tests
Water Zig-zag Test: As described in the land zig-zag tests, the water zig-zag
tests were performed using a combination of differential thrust commands. The GPS,
IMU, compass and motor controllers were used to collect data during the test.
The vehicle started at full speed before the open loop zig-zag maneuver was
initiated. Differential motor commands of 70/40, 110/70, 110/80 and 122/100 were
used. Typically a zig-zag test uses rudder deflections of 10-20 [deg], however these
tests used a variety of deflections.
119
Below is an example of the motor command data and a plot of the vehicle’s
position in Google Earth during the water zig-zag test for motor commands of 122 and
0. This data was used for systems identification, which is described in Section 3.2.
150
Port
Starboard
Motor Command
100
50
0
80
100
120
140
Time [sec]
160
Figure 69 - 122/0 Water Zig-Zag Motor Commands
120
180
200
Fiigure 70 - Veh
hicle Position iin Water Zig-zzag Test
3.2
System
ms Identificaation
Perfforming the zig-zag
z
test gave
g
data thaat is useful ffor systems iidentificationn. By
measuring the
t motor co
ommand inp
puts, as welll as the IMU
U outputs ffor velocitiess and
yaw rate, a model
m
can be
b estimated based on thhe relationshiip between tthe two measured
sets of data. Systems ideentification was
w perform
med for both land and waater.
ms ID toolb
box was ussed for systtems identiffication withh the
Matllab’s System
collected daata, which is a built in to
oolbox that ccontains a grraphical userr interface (G
GUI).
The data waas clipped to
o contain on
nly the time the vehiclee was perforrming the zigg-zag
pattern, and
d not when itt was accelerrating to steaady state, orr after the zigg-zag patternn was
executed.
1221
The data collectted from th
he IMU duriing the zig-zag tests was in earth fixed
coordinates.. To convertt the velocities into the bbody fixed frrame, the earrth fixed vellocity
matrix was multiplied
m
by
b the transfo
ormation maatrix below, w
where
is tthe yaw anglle.
Thiss complete transformatio
t
on is seen iin the Matlaab code in A
Appendix B
B. 8In
addition to converting the measureements into the body fixxed coordinnate frame, tthe X
and Y veloccities also neeeded to be transformed
t
from the loccation of meeasurement tto the
location of the
t center off floatation, the position in which thhe vehicle pivvots around.. This
transformatiion was perrformed witth the follow
wing equation, where tthe new vellocity
matrix,
, is
i found by subtracting
g the cross pproduct of tthe roll, pittch and yaw
w rate
matrix,
, and
a the location matrix of
o the sensor from the ceenter of floattation, .
Afteer the velociities were trransformed into the boody fixed cooordinate syystem,
they were used as outpu
uts in the sysstems identiffication toolbbox.
w
the poort and starbboard motorr commandss. As
The inputs for the model were
stated earlieer, only thee data colleected after tthe vehicle had reacheed a steady state
straight-linee course and then initiateed the maneuuver was used for system
ms identificaation.
To estimate a model, a third
t
order liinear parameetric state sppace model w
was used.
1222
Below are the motor command inputs, and the u,v, and yaw rate outputs of the
1250 water zig-zag test, with an overlay of the final model that was obtained on the
outputs.
150
Port
Starboard
Motor Command
100
50
0
0
10
20
30
40
50
60
Figure 71- Motor Commands Land Zig-zag for Systems ID
1
0.95
Body u Velocity [m/s]
0.9
0.85
0.8
0.75
0.7
0.65
Model
Measured IMU Data
0.6
0.55
0
10
20
30
40
50
Time [sec]
Figure 72 - Body Fixed u Velocity Model-Black Signal is the Measured Velocity
123
60
0.1
0.05
Body v Velocity [m/s]
0
-0.05
-0.1
-0.15
-0.2
-0.25
-0.3
Model
Measured IMU Data
-0.35
-0.4
0
10
20
30
40
50
60
Time [sec]
Figure 73 - Body Fixed v Velocity Model-Black Signal is the Measured Velocity
0.1
Yaw Rate
0.05
0
-0.05
-0.1
-0.15
0
Model
Measurd IMU Data
10
20
30
40
50
60
Time [sec]
Figure 74 - Yaw Rate Model-Black Signal is the Measured Yaw Rate
A second data was used to compare the model to this second set of inputs and
outputs. Below is the motor command inputs for the 100/0 zig-zag water test, and the
corresponding outputs with the model estimate overlaid on the output data.
124
0.75
0.7
Body u Velocity
0.65
0.6
0.55
Model
Measured IMU Data
0.5
0.45
0
5
10
15
20
15
30
35
Time [sec]
Figure 75 - Body u Velocity Model on Second Data-Black Signal is Measured Velocity
0.7
0.65
Model
Measured IMU Data
Body v Velocity [m/s]
0.6
0.55
0.5
0.45
0.4
0.35
0
5
10
15
20
25
30
35
Time [sec]
Figure 76 - Body v Velocity Model on Second Data-Black Signal is Measured Velocity
125
0.15
0.1
Yaw Rate [deg/sec]
0.05
0
-0.05
-0.1
Model
Measured IMU Data
-0.15
-0.2
0
5
10
15
20
25
30
35
Time [sec]
Figure 77 - Yaw Rate Model on Second Data-Black Signal is Measured Yaw Rate
It was found the model is a close fit for the u and v velocity predictions,
however the yaw rate prediction is a significantly better result when the data is
compared to the model in both cases. This finding is important for future autonomous
control, because the yaw rate output is most useful in autonomous control, especially
for a slow moving vehicle such as the DUKW. The third order state space model is
shown below. In the equation, x(t) is the state vector and u(t) is the control vector.
126
1.0001
8.67 10
.00043
.00192
.011992
. 00281
. 00012
1.0003
.00048
. 00847
.00579
. 00247
4.59 10
7.085 10
. 99651
+
7.47 10
1.3641 10
9.2162 10
3.71 10
1.2559 10
5.6677 10
u(t)+
.00315
. 00541
. 04215
6.700
26.993
1.524
27.676 1.227
8.461 1.342
1.084
3.990
0 0
0 0
0 0
x(0) =
x1 = 0.01213
x2 = -0.02238
x3 = -0.00671
For the land test, the same procedure was used. However, the predicted bodyfixed velocities and yaw rate do not match the measured values well. It is believed that
the bumpy, sandy ground was the reason for this noisy looking signal. Another factor
that affected this test was the limited space available for testing. The sandy area on
Seatech property was used because it is mostly level, unlike the beach which has a
constant slope. The downside to this test region is the fact that the vehicle could not
make large turns as it could in the water tests. It also could not be driven very long in
the forward direction to achieve a steady state motion because of the limited space. The
beach would give more space for this test, but no area of the beach could be found that
was flat enough to perform this test without dealing with the inconsistencies with the
beach slope.
127
Because of the limitations in test conditions, if a better model is required for
autonomous control, these tests should be redone at a location that has a large sandy
area, but does not contain a slope as found on most beaches in the area.
1.6
1.4
u Velocity [m/s]
1.2
1
0.8
0.6
0.4
0.2
0
5
10
15
Time [sec]
Figure 78 - Body Fixed v Velocity Land Model-Black Signal is Measured Velocity
1.5
v Velocity [m/s]
1
0.5
0
-0.5
-1
0
5
10
Time [sec]
Figure 79 - Body Fixed v Velocity Model Land-Black Signal is Measured Velocity
128
15
0.4
0.3
Yaw Rate [rad/sec]
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
0
5
10
15
Time [sec]
Figure 80 - Yaw Rate Model Land-Black Signal is Measured Yaw Rate
The land model is shown below. It is suggested that to estimate a better model
for this data, these tests be performed in a larger test area so the turns can be executed
for longer than 3 seconds each. The water tests used 10 second turns, which proved to
give a data that was easier to fit a model to. The accuracy of this model was affected by
the test conditions. Again, a third order state space model was used, and it is shown
below.
129
. 9979
.0048
.0113
. 002
29
. 994
44
. 004
49
. 0082
.0014
. 9962
3.5427
4.3959
6.8854
+
. 0010
4.117 10
.0008
8
5.9176
5
3.8696
.0205
5.8133
3.1278
. 1213
. 0005
. 0007 uu(t)+
.0010
0
0
0
.0027
.0106
.0145
.0067
. 0204
.0445
. 078
83
.012
28
. 065
54
0
0
0
x(0) =
x1 = -0.0201
1
x2 = 0.0308
x3 = -0.1125
5
3.3
Transition Region
n Tests
The transition teests are one of the mosst important parts of this thesis, as these
tests provide data to und
derstand the unknown arreas of the vvehicle concept developm
ment.
The vehicle was driven open loop through
t
the ttransition region, both toowards and away
from shore.. Its motions while in the
t breakingg wave areaa of the surff zone weree also
recorded, to
o help betterr understand
d what the vvehicle will experience while naviggating
through thiss dynamic reegion.
The vehicle starrted on the beach,
b
and w
was given ann open loop motor comm
mand
for 30 secon
nds, approacching the su
urf zone perppendicularlyy. Once the vvehicle was fully
buoyant, an
nd at a depth
h where it waas no longerr making conntact with thhe ground, it was
left to be su
ubjected to th
he breaking waves
w
in thee surf zone, while its mootions were bbeing
recorded. Fiinally, the veehicle faced the beach, aand was giveen the same m
motor comm
mands
as on its waay out, and it
i ran this 30
0 second oppen loop pathh onto the bbeach. Durinng the
tests, the mo
otor current was recordeed so the drivvetrain forcees could be qquantified dduring
1330
its beach traansition. Mo
otor comman
nds of 80, 900, 100, 110 aand 125 to bboth motors were
used for testting.
Thesse three situ
uations, land
d-to-sea, seaa-to-land, aand the vehiicle subjecteed to
breaking waaves in the surf
s zone weere each testeed, and the rresults will bbe split into these
three catego
ories.
Wav
ve Characteeristics
It is important to
o define the wave charaacteristics duuring these trransition tessts, so
the motions found in tessting can be related to thhe waves thee vehicle expperienced. F
Figure
79 shows tw
wo pictures of
o the ocean
n on the day tthe tests werre performedd.
Figure 81 - Dania
D
Beach O
Ocean on Testt Day
To quantitativel
q
ly define th
he wave ch aracteristics during testing, two O
Ocean
Sensor Systtems wave staffs
s
were installed in the surf zone to measuure the incooming
waves. These capacitan
nce wave gaauges measuure the waterr location allong their leength.
Typical caliibration of these sensorrs when useed in a wavve tank is to locate thee still
1331
waterline location, and use this as a zero location. However, because these tests were
performed in a non-controlled environment, this calibration was not possible. Instead,
the average value over the entire test was used as a zero location, and wave amplitudes
were measured from this point. While this is not as precise as the previous method of
calibration, it was the only way the median level could be located.
The wave staffs were placed in the location that the vehicle was tested in the
surf zone motion tests. The sensors use an RS232 communication and the data was
collected with a laptop. An example of this data is shown in the figure below. The staff
is 500 [mm] long, and the data is output as number of counts from the bottom of the
staff. The Matlab code converts the count output into a distance in [mm] from the
bottom using the width of each wire wrap. The break in data is due to the combination
of two sets of data, and a time difference between the end time and start time.
500
Gauge 1
Gauge 2
450
Waterline Location [mm]
400
350
300
250
200
150
100
50
0
0
50
100
150
200
Time
Figure 82 - Wave Gauge Output
132
250
300
350
These water level locations were converted to wave amplitude by first finding
the average value of the data, which was set to the mean waterline, or zero, of the data.
Then the amplitudes were calculated from this level. The figure below is the data after
the mean waterline was subtracted from the entire set of data. The Y-axis shows the
water position from the mean water level over the course of the test. The gauges were
mounted in a line perpendicular to the beach, where the first gauge was at the point the
waves were beginning to break and the second in the region the waves had already
broke. This was about 20 and 30 feet from the tideline, in depths of about 2.5 and 3 feet,
for the first and second gauge, respectively. The waves were measured for a duration of
15 minutes. Because of the sample time, the tide level remained constant for the tests.
The wave gauges measured at 20 [Hz].
350
300
Waterline Location [mm]
250
200
150
100
50
0
-50
-100
-150
0
1000
2000
3000
4000
Figure 83 - Wave Data in Surf Zone Tests
133
5000
6000
7000
To characterize
c
the waves present
p
in thhe test area during the experimentss, the
significant wave
w
heightt was used. This is the average valuue of the laargest 1/3rd oof the
measured am
mplitudes. This
T was calcculated for bboth wave gaauges, and thhe process can be
seen in the Matlab
M
sectiion of the ap
ppendix. Thee significant wave heightt was found to be
27.92 [cm]. This value makes it possible to now
w relate the measured m
motions desccribed
below to waave characterristics seen in
i the surf zoone.
3.3.1
Land
d-to-Sea
As described
d
above, the veh
hicle started facing the oocean and w
was given a m
motor
command to
o the tracks for
f 30 secon
nds, which w
was equal to bboth port andd starboard.
The first motorr command combinationn was 80, w
which is abbout 65% off full
power. The results of th
his test are sh
hown in the figures beloow. The X-axxis timescalees are
synchronizeed so the IM
MU motions and motor ddata can be compared eeasily. The eentire
collection of these resullts can be fo
ound in the aappendix. It should be nnoted that alll tests
looked very
y similar to th
he one show
wn below, so it was unnecessary to display each set of
data in the main
m
text. A table with average valuues is providded describiing the full rrange
of tests.
1334
Motor Command
100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
600
400
200
0
600
400
200
0
Roll [deg]
Figure 84 - Land-to-Sea Transition Motor Data (Motor Command: 80)
5
0
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-5
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
0.5
0
-0.5
Figure 85 - Land-to-Sea Transition Motions (Motor Command: 80)
Looking at the data above, it can be seen that when the motors are given the
command of 80, the track force is at its highest, an average of 494 [N] between port and
135
starboard, which
w
meanss it takes ab
bout 1000 [N
N] to start tthe vehicle from rest inn this
situation. This
T
is very close to th
he 1068 [N]] estimate uused in gearring calculattions,
shown in th
he drivetrain gearing dessign section. The vehiclee was startedd at a positioon on
the beach th
hat aimed to make the trransition from
m land to seea about halfway througgh the
30 second test,
t
which was
w about 50
0 feet from the waterlinne. Figure 844 is the vehicle’s
position plo
otted in Goog
gle Earth. Note the tide was not the same as shoown in the fiigure,
so the waterrline is not th
he same as itt was on the day of the ttest.
Figure 86 - Beach-to-Seea Vehicle Traack
Afteer the initial momentum
m is obtainedd, the track fforce stays ffairly constaant to
about 20 seeconds into the
t test, wheere it beginss to fall. At this point, bby looking aat the
IMU motion
n data, it can
n be seen thaat the vehiclee is in contaact with wavves because oof the
sinusoidal motions
m
it beegins to exp
perience exacctly at the tiime the trackk force begiins to
decrease. Th
his drop in force
f
on the tracks can bbe contributeed to the facct that the veehicle
is obtaining
g a buoyanccy force as it enters thhe water annd begins too experience the
1336
motions of the waves. The effective weight of the vehicle is less because of this
buoyancy force, and therefore we see a drop in the track force measured. The
intermittent jumps in track force during the few seconds the vehicle is between fully
land and fully buoyant can be attributed to the tracks coming into contact with the
bottom as waves cause it to heave.
About 5 seconds after its initial motions from encountering the water, or at 25
seconds into the test, the heave and roll motions become noticeably larger, and the track
force falls off to almost zero. The reason the force does not fall all the way to zero is
due to the manner in which the force is being calculated. The current to the motors is
used to determine a resulting force, and since the drivetrain still provides some
resistance even when the vehicle is floating, the current does not fall enough for the
calculated force to be zero, because the motor is still drawing some current.
The exact instant that the vehicle transitions from land to sea and becomes
completely supported by a buoyant force is nearly impossible to determine, both
because of the nature of the test conditions as well as the fact that the vehicle is
subjected to waves which means it is coming into contact with the ground even after it
has been supported by a buoyant force. Because of this, it is difficult to determine an
exact force when the vehicle is on land, or in the surf zone. However, splitting this test
in half, and taking the average of the force measured for each half gives a reasonable
estimate of the average force on land, and an average force while transitioning. These
values were documented by CISD as a necessary unknown that needed to be defined.
137
Belo
ow is a tablee of the forces measuredd during the transition ffrom beach tto the
ocean, throu
ugh the surff zone. As would
w
be exxpected, the first leg off these tests gave
forces that were,
w
on aveerage, about 3.5 times thhe forces meeasured whenn the vehiclee was
in contact with
w the wateer. The buoy
yant force thhat resulted ffrom the vehhicle drivingg into
the water significantly reduced
r
the force requirred to drive tthrough this region. It shhould
be noted th
hat the maxiimum force measured during the entire test iis less than 15%
greater than
n the estimatted design reesistance forrce used to ddesign the ddrivetrain geearing
system.
Table
T
27 - Lan
nd-to-Sea Drivvetrain Force R
Results
Motor Commaand Average FFull Test [N] Avverage First Half [N] Average
e Second Half [N
N] Maximum FForce [N]
171.17
80
112.58
50.70
220.2
29
228.70
90
144
54.99
4.86
530.3
35
200.16
100
36.35
11
19.06
685.3
37
248.96
110
60.25
15
53.89
840.4
40
257.30
125
127.03
19
99.58
832.2
23
221.26
All Tests
65.86
145.99
621.7
73
3.3.2
Sea--to-Land
The next set of data collectted was the vehicle appproaching thhe shoreline. The
mands used above were again used in this direcction. The veehicle
same set of motor comm
started in th
he ocean an
nd approacheed the surf zzone and m
made its wayy onto the bbeach,
again open loop for 30
0 seconds at equal motoor commandds to both poort and starbboard
tracks. The test was starrted perpend
dicular to thee shore, in a water depthh of about 3 feet,
which was an
a extra foott of water un
nder the vehhicle draft, too ensure therre was no coontact
with the gro
ound at the beginning
b
off the test. Thhe 3 foot waater depth w
where the test was
started was about 40 feet
f
from th
he tide line. The test w
was initiated when the m
motor
1338
commands were
w sent to the tracks, and
a as soon as the vehiccle came intoo contact witth the
sand it begaan to drive on
nto the beacch. Figure 844 shows the vehicle’s poosition durinng the
sea-to-land test. Again, as above, th
he tide line iss not the sam
me in the Gooogle Earth im
mage
as it was on test day, so the waterlin
ne location iss not exact.
Figure 87 – Sea-to-Land
d Vehicle Traack
Belo
ow is a set off data during
g the sea-to-lland transition. For conssistency, thiss data
in figure 86 is the samee 80 motor co
ommand as the plots shown above iin the land-tto-sea
transition.
1339
Motor Command
100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
400
300
200
100
0
600
400
200
0
Figure 88 – Sea-to-Land Transition Motor Data (Motor Command: 80)
Roll [deg]
10
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-10
1
0
-1
Figure 89 - Sea-to-Land Transition Motions (Motor Command: 80)
As would be expected, the opposite results were found compared to the land-tosea transition. The vehicle experiences large motions initially, and as it comes into
140
shallower water, and contacts the bottom, the motions decay to zero as it is no longer
buoyant and experiencing motions from the surf zone waves. The vehicle experiences
no wave motions after about 15 seconds. Looking at the motor data just before this
occurs, it can be seen that the force fluctuates due to the heaving motion and the
intermittent track contact with the bottom before it is fully out of the water and in full
contact with the ground.
Again, as described above, it is impossible to choose a point at which the vehicle
transitions between sea and land, because of the motions that cause it to come in contact
with the bottom as it approaches the beach, and because of the unpredictability of the
test area. Therefore, the test can be split in half and averages can be taken of the
drivetrain forces required in the transition.
Below is a table showing the average forces found through the whole range of
tests. Again, as would be expected, the first half of the test, when the vehicle is partially
buoyant, the forces are much less than when the vehicle is fully on land.
Table 28 – Sea to Land Drivetrain Force Results
Motor Command Average Full Test [N] Average First Half [N] Average Second Half [N] Maximum Force [N]
80
167.37
115.71
208.06
407.96
90
251.10
205.25
268.25
481.39
100
233.15
103.66
343.66
246.66
110
247.88
192.04
278.34
522.19
125
286.18
249.57
273.48
856.72
All Tests
237.14
173.25
274.36
502.98
141
3.3.3
Vehiicle in the Su
urf-Zone
Betw
ween the lan
nd-to-sea an
nd sea-to-lannd tests, the vehicle waas left in thee surf
zone and experienced
e
the breakin
ng waves foound in thiss area. Becaause autonom
mous
vehicles hav
ve traditionaally not traveersed this reggion, the mootions the vehhicle experieences
in the regio
on are imporrtant in systeem developm
ment. It is difficult to aaccurately m
model
the waves th
he vehicle iss experiencing during thhis test, but the average wave condiitions
can be relatted to the motions
m
the vehicle
v
expeeriences durring the test.. This provides a
rough estim
mate of the motions
m
the vehicle can bbe expected tto experience in the surff zone
region when
n it is autono
omous.
Figu
ures 88-92 below
b
show the vehicle ’s motions iin the surf zzone for thee five
Yaw Rate [deg/sec]
Roll Angle [deg]
Pitch Angle [deg] Heave Velocity [m/s]
separate testts.
0.5
0
-0.5
0
10
0
20
30
Time [se
ec]
40
50
60
0
10
0
20
30
Time [se
ec]
40
50
60
0
10
0
20
30
Time [se
ec]
40
50
60
0
10
0
20
30
Time [se
ec]
40
50
60
20
0
-20
20
0
-20
20
0
-20
Figure 90 - Motions
M
in thee Surf Zone T
Test 1
1442
Pitch Angle [deg] Heave Velocity [m/s]
1
0.5
0
0
5
10
15
20
25
30
35
40
45
25
30
35
40
45
25
30
35
40
45
25
30
35
40
45
Time [sec]
20
0
-20
0
5
10
15
20
Yaw Rate [deg/sec]
Roll Angle [deg]
Time [sec]
10
0
-10
0
5
10
15
20
Time [sec]
50
0
-50
0
5
10
15
20
Time [sec]
Pitch Angle [deg] Heave Velocity [m/s]
Figure 91 - Motions in the Surf Zone Test 2
1
0.5
0
0
5
10
15
20
25
30
35
40
45
25
30
35
40
45
25
30
35
40
45
25
30
35
40
45
Time [sec]
20
0
-20
0
5
10
15
20
Yaw Rate [deg/sec]
Roll Angle [deg]
Time [sec]
5
0
-5
0
5
10
15
20
Time [sec]
50
0
-50
0
5
10
15
20
Time [sec]
Figure 92 - Motions in the Surf Zone Test 3
143
Heave Velocity [m/s]
Pitch Angle [deg]
1
0
-1
0
10
20
30
40
50
60
70
80
90
50
60
70
80
90
50
60
70
80
90
50
60
70
80
90
Time [sec]
20
0
-20
0
10
20
30
40
Yaw Rate [deg/sec]
Roll Angle [deg]
Time [sec]
10
0
-10
0
10
20
30
40
Time [sec]
50
0
-50
0
10
20
30
40
Time [sec]
Pitch Angle [deg]
Heave Velocity [m/s]
Figure 93 - Motions in the Surf Zone Test 4
1
0
-1
0
10
20
30
40
50
60
70
40
50
60
70
40
50
60
70
40
50
60
70
Time [sec]
10
0
-10
0
10
20
30
Yaw Rate [deg/sec]
Roll Angle [deg]
Time [sec]
10
0
-10
0
10
20
30
Time [sec]
50
0
-50
0
10
20
30
Time [sec]
Figure 94 - Motions in the Surf Zone Test 5
While it may be difficult to compare these motions to one another, taking the
average of the absolute value measured for each motion gives a better number to
144
compare among the different tests. Below are tables of the average values found in each
test. It was found the averages were very similar from test to test, as seen in Table 34
below, the variance between all the tests is low for all motions. The average motions for
all tests are shown in Tables 29-33.
Table 29 - Average Motions Test 1
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average of All Tests
0.35
3.74
2.41
5.08
Variance
0.0367
5.2549
3.9941
18.0216
Table 30 - Average Motions Test 2
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average Value During Test
0.51
3.82
1.87
5.87
Variance
0.0283
5.6740
1.6720
18.4664
Table 31 - Average Motions Test 3
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average Value During Test
0.53
3.79
1.75
4.77
Variance
0.0379
5.4235
1.3810
21.1209
Table 32 - Average Motions Test 4
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average Value During Test
0.44
4.18
2.10
4.48
145
Variance
0.0283
7.8703
2.3414
20.8922
Table 33 - Average Motions Test 5
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average Value During Test
0.40
3.54
1.97
4.54
Variance
0.0267
4.5842
1.9007
21.1076
From the averages found in the tables above, it can be seen that the motions stay
very consistent throughout the five tests. Table 34 below is the averages of all the test
results, it can be seen that the variance of measured motions is extremely low for each
value. These motions below show the average expected motions for a vehicle in this
type of surf zone waves. Although conditions constantly change, having this data
relating wave characteristics to vehicle motions can help predict motions in different
wave conditions, and also gives future test developers an idea of the response
characteristics of this vehicle.
Table 34 - Average of all Surf Zone Motion Test Results
Measurement Heave Velocity [m/s]
Pitch Angle [deg]
Roll Angle [deg]
Yaw Rate [deg/sec]
Average of All Tests
0.45
3.81
2.02
4.95
Varience
0.0059
0.0538
0.0641
0.3212
In order to further characterize the surf zone and the vehicle motions in the surf
zone, the data were transformed into the frequency domain to locate dominant
frequencies found in the incoming waves as well as the response of the vehicle.
First looking at the waves, and zooming in on a 20 second window, as shown in
figure 95 below, the multiple frequencies can be seen.
146
250
200
Wave Height [mm]
150
100
50
0
-50
-100
-150
-200
-250
0
2
4
6
8
10
Time [sec]
12
14
16
18
20
Figure 95 - Waves in a 20 Second Period
Looking at the dominant frequencies in figure 96, we find peaks at frequencies
of 0.1172 [Hz], 0.2344 [Hz], 0.4688 [Hz] and 0.5469 [Hz]. In the time domain, these
correspond to periods of 8.532 [sec], 4.266 [sec], 2.133 [sec] and 1.828 [sec]. The first
three periods are half of the previous value, showing that they are harmonics. These
periods can be seen in figure 95, as we see peaks occurring at these intervals.
147
5
3
x 10
2.5
2
1.5
1
0.5
0
0
0.5
1
1.5
Frequency (Hz)
Figure 96 - Wave Frequency in Surf-zone
Now, looking at the vehicle’s frequency response to these incoming waves, can
be seen in figure 97 below.
Heave
50
Pitch
0
0
2
3
4
5
6
1
2
3
4
5
6
1
2
3
Omega
4
5
6
500
0
0
Roll
1
500
0
0
Figure 97 - Roll, Pitch and Heave Frequency Response to Surfzone
148
3.4
Froud
de-Krylov Ex
xcitation Forrces
To estimate
e
the wave excitaation forces acting on tthe vehicle iin shallow w
water,
the Froude-K
Krylov apprroach can be used. Thesee pressure foorces are fouund by integrrating
the pressuree over the mean
m
wetted surface of tthe hull. Thiis was done using the m
model
DUKW-ling
g’s dimensio
ons in head
d seas (wherre the anglee the vehiclle encounterrs the
waves, β=0)) and the ressults are sho
own below [36]. This giives an estim
mate of the fforces
and momen
nts that cou
uld be experrienced in tthe surf zonne. Below iis Froude-K
Krylov
method used
d to estimatee excitation forces
f
and m
moments in a water depthh of 0.61 [m
m].
F1 [N]
500
0
0
-500
0
0
F2 [N]
2
x 10
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
Time [sec]
T
5
6
7
8
-13
0
-2
2
0
F3 [N]
1000
0
0
-1000
0
0
Figurre 98 - Surge (1),
( Sway (2), H
Heave (3) Forrce vs. Time
1449
F4 [N-m]
1
0
-1
0
1
2
3
4
5
6
7
8
1
2
3
4
5
6
7
8
1
2
3
4
Time [sec]
5
6
7
8
F5 [N-m]
1000
0
-1000
0
F6 [N-m]
2
x 10
-13
0
-2
0
Figure 99 - Roll (4), Pitch (5), Yaw (6) Moments vs. Time
150
4
CONCULU
USIONS
Thiss project aim
med at defin
ning unknow
wns about thhe DUKW-ling autonom
mous
amphibious vehicle con
ncept. Traveling througgh the surf zone is a new area foor an
autonomouss vehicle, an
nd an area that is very dyynamic and ddifficult to m
model. Thereefore,
experimentaal testing with
w
the veh
hicle model was the iddeal approacch to definee the
unknowns th
hat were affe
fecting the co
ontinued devvelopment off this projectt.
The vehicle’s motions
m
in thee surf zone, tthe drivetraiin forces reqquired to navvigate
one, its driiving charaacteristics suuch as turnning radiuss, velocitiess and
the surf zo
acceleration
ns were docu
umented by CISD as unnknowns thaat were needded for algorrithm
developmen
nt being con
nducted theree. The minim
mum turningg radius on lland was 2.44 [m]
(about one vehicle
v
leng
gth), the max
ximum velocity was 1.991 [m/s] andd the accelerration
was 0.93 [m
m/s2]. In waater, the min
nimum turniing radius w
was found too be less thaan on
land, 1.93 [m], and water
w
maxim
mum velociity was 1.119 [m/s], w
with a maxiimum
acceleration
n of 1.98 [m
m/s2]. The yaaw rates for different m
motor commaands to bothh land
and water motors
m
weree found so autonomouus control deevelopment has quantittative
values for th
he different motor
m
inputss that can bee used in navvigation.
It was
w found th
hat in a sign
nificant wavee height of 28 [cm], thhe average hheave
velocity was 0.45 [m/s], which is allmost half oof the vehiclee’s maximum
m forward speed.
It experiencces average pitch and roll
r
angles of 3.81 andd 2.02 degreees, respectiively.
These anglees are more than doublee those founnd when thee vehicle peerforms a zigg-zag
1552
maneuver or
o turning cirrcle test. An
n average yaaw rate of 44.95 degreess/second how
wever
was the sam
me as was fo
ound when the
t vehicle w
was perform
ming a very wide turn w
with a
radius of 8.56 meters, where
w
the vehicle’s minnimum turniing radius iss 4.92 meterrs. So
although thee vehicle ex
xperiences laarge pitch annd roll motioons, it is able to maintaain its
heading wheen encounterring the breaaking wavess.
Wheen navigating the surf zone region, the force onn the tracks was found to be
250 [N] to each track on
o average when
w
on lannd, and moree than half oof that whenn it is
bmerged. Th
he maximum
m force was 6621 [N] andd was found when the veehicle
partially sub
was going from
f
land-to
o-sea, and go
oing from seea-to-land, thhe maximum
m value was 80%
less.
In addition
a
to finding
f
the unknowns that were ddocumentedd as setbackks for
algorithm development,
d
, a model fo
or both land and sea navvigation wass found baseed on
maneuverin
ng test data. This
T model can
c be a starrting point fo
for future auttonomous coontrol
efforts.
4.1
mmendations for Future Work
Recom
Thiss project is continuing
c
at
a FAU withh present graaduate studeent Jose Alvvarez.
This thesis work aim
med at providing him with a com
mplete set of data annd an
understandin
ng of vehiccle performaance througgh experimeental testing. The driveetrain,
electronics and sensor systems
s
werre all used tto perform m
months of teesting, and m
minor
changes werre made untiil the vehiclee’s performaance was devveloped intoo a robust, eaasy to
use platform
m. Becausee of this work,
w
the veehicle is being turnedd over to ffuture
1553
researchers in a state that they will need to focus no time on the vehicle systems, and
rather focus their efforts on autonomous development.
Future work outside of the autonomous control system work going on presently
at FAU can be broken into three categories: vehicle model, surf zone testing and full
scale mechanical design.
In terms of the vehicle model, the only set back this work has found is a lack of
motor power. Both the land and water motors should be upgraded as the vehicle is
underpowered in both regards. During tests, the land motors were found to exceed their
current limit significantly in certain situations. This can cause damage in the long term,
and these can be replaced with minimum complexity because of their easy access
location on the vehicle. The propeller motors are also underpowered. The vehicle is
difficult to control in the water, mainly because of the low thrust output available from
the propellers. In the surf zone, the vehicle will need significant thrust to overcome
wave forces, and these motors will not provide that thrust. The vehicle’s turning radius
will also improve with more thrust available.
In terms of surf zone testing, it is recommended to continue the surf zone
transition tests in a variety of surf conditions, while again measuring the waves present
in the surf zone. Having a broad set of data will be useful for this concept, as well as
future research that might deal with a vehicle traveling through the surf zone or
breaking waves.
The full scale vehicle design will require more testing in the surf zone to further
define the forces acting on the vehicle, both from slamming motions as well as contact
with the bottom. Structural tests should be completed to understand the amount of
154
forces the full scale vehicle might experience when in navigates this surf zone region
continuously during a cargo transport mission.
155
5
APPEN
NDIX
A. All test resu
ults
Transition Te
ests: Motor Command
 Moto
or Command:: 80 Land‐to‐Sea 100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
2
25
30
35
40
0
5
10
15
20
Time [sec]
2
25
30
35
40
0
5
10
15
20
Time [sec]
2
25
30
35
40
600
400
200
0
600
400
200
0
1556
Roll [deg]
5
0
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-5
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
1
0.5
0
Motor Command
Sea‐to‐Land 100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
400
300
200
100
0
600
400
200
0
157
Roll [deg]
10
0
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-10
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
0.5
0
-0.5
Motor Command
 Motor Command: 90 Land‐to‐Sea 100
50
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
600
400
200
0
0
5
10
15
20
25
30
35
20
25
30
35
Stbd Track Force [N]
Time [sec]
800
600
400
200
0
0
5
10
15
Time [sec]
158
Roll [deg]
5
0
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-5
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
1
0.5
0
Motor Command
Sea‐to‐Land 100
50
0
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
Port Track Force [N]
Time [sec]
400
300
200
100
0
0
5
10
15
Stbd Track Force [N]
Time [sec]
600
400
200
0
0
5
10
15
Time [sec]
159
Roll [deg]
10
0
-10
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
20
25
30
35
Yaw Rate[deg/sec]
Pitch [deg]
Time [sec]
20
0
-20
0
5
10
15
Time [sec]
0.5
0
-0.5
0
5
10
15
Heave Vel. [m/s]
Time [sec]
1
0.5
0
0
5
10
15
Time [sec]
Motor Command
 Motor Command: 100 Land‐to‐Sea 100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
800
600
400
200
0
800
600
400
200
0
160
Roll [deg]
10
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
10
0
-10
0.5
0
-0.5
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-10
2
1
0
Motor Command
Sea‐to‐Land 150
100
50
0
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
Port Track Force [N]
Time [sec]
600
400
200
0
0
5
10
15
Stbd Track Force [N]
Time [sec]
600
400
200
0
0
5
10
15
Time [sec]
161
Roll [deg]
10
0
-10
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
20
25
30
35
Yaw Rate[deg/sec]
Pitch [deg]
Time [sec]
20
0
-20
0
5
10
15
Time [sec]
0.5
0
-0.5
0
5
10
15
Heave Vel. [m/s]
Time [sec]
1
0.5
0
0
5
10
15
Time [sec]

Motor Command: 110 Land‐to‐Sea 162
Motor Command
100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
0
5
10
15
20
Time [sec]
25
30
35
40
1000
500
0
1000
500
0
Roll [deg]
10
0
10
0
-10
0.5
0
-0.5
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-10
1
0
-1
Sea‐to‐Land 163
Motor Command
150
100
50
0
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
Port Track Force [N]
Time [sec]
600
400
200
0
0
5
10
15
Stbd Track Force [N]
Time [sec]
600
400
200
0
0
5
10
15
Time [sec]
Roll [deg]
10
0
-10
0
5
10
15
20
25
30
35
20
25
30
35
20
25
30
35
20
25
30
35
Yaw Rate[deg/sec]
Pitch [deg]
Time [sec]
20
0
-20
0
5
10
15
Time [sec]
0.5
0
-0.5
0
5
10
15
Heave Vel. [m/s]
Time [sec]
1
0.5
0
0
5
10
15
Time [sec]
 Motor Command: 125 Land‐to‐Sea 164
Motor Command
100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
1000
500
0
1000
500
0
Roll [deg]
10
0
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
10
0
-10
0.5
0
-0.5
Heave Vel. [m/s]
Yaw Rate[deg/sec]
Pitch [deg]
-10
1
0
-1
Sea‐to‐Land 165
Motor Command
150
100
50
Stbd Track Force [N]
Port Track Force [N]
0
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
800
600
400
200
0
1000
500
0
Roll [deg]
10
0
Heave Vel. [m/s]
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
0
5
10
15
Time [sec]
20
25
30
10
0
-10
Yaw Rate[deg/sec]
Pitch [deg]
-10
1
0
-1
1
0.5
0
166
Land Circle Tests: Left Turn 60
40
Stbd Cmd
Track Force [N]
20
30
40
50
60
70
60
50
20
15
40
10
30
20
5
0
10
20
30
40
50
60
0
70
56
55.5
40
30
55
20
54.5
54
10
0
10
20
30
0
0
10
20
30
40
50
60
40
50
60
0
70
Current [amps]
10
Current [amps]
20
0
Port Cmd
Motor Cmd
55 Starboard, 35 Port 400
200
Velocity [m/s]
GPS Yaw Rate [deg/sec]
Time [sec]
Unwrapped Heading [deg]

70
Port
Starboard
0
-5
-10
0
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
1
0.5
0
0
200
0
-200
0
10
20
30
40
50
60
70
Time [sec]
167
Roll [deg]
Pitch [deg]
Yaw Rate [rad/sec] Yaw [deg]
2
0
-2
2
0
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
5
0
-5
5
0
200
0
0
-200
0
0
0.5
5
0
-0.5
5
0
Position [m]
15
10
5
0
0

Port 75 Sttarboard, 35 P
1668
5
10
0
Position [m]
15
5
Motor Cmd
100
50
40
50
60
70
80
40
50
20
0
10
20
30
40
50
60
70
0
80
Current [amps]
30
100
0
Stbd Cmd
Track Force [N]
20
76
100
75
50
74
0
10
20
30
40
50
60
70
0
0
10
20
30
40
Time [sec]
50
60
70
0
80
GPS Yaw Rate [deg/sec]
500
Velocity [m/s]
Unwrapped Heading [deg]
10
Current [amps]
Port Cmd
0
0
80
Port
Starboard
10
0
-10
-20
0
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
1.5
1
0.5
0
0
500
0
-500
-1000
0
169
Roll [deg]
Pitch [deg]
Yaw Rate [rad/sec] Yaw [deg]
2
0
-2
2
0
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
5
0
-5
5
0
200
0
0
-200
0
0
0.5
5
0
-0.5
5
0
10
0
Position [m]
8
6
4
2
0
0

75 Sttarboard, 45 P
Port 1770
2
4
6
Position [m]
8
10
GPS Yaw Rate [deg/sec]
Velocity [m/s]
Unwrapped Heading [deg]
10
0
-10
-20
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
Time [sec]
1.5
1
0.5
0
0
20
40
60
Time [sec]
500
0
-500
-1000
0
20
40
60
Time [sec]
Roll [deg]
4
2
0
-2
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
Time [sec]
Pitch [deg]
2
0
-2
-4
0
20
40
60
Time [sec]
Yaw [deg]
200
0
-200
0
20
40
60
Time [sec]
171
Yaw Rate [rad/sec]
0.5
5
0
-0.5
5
0
20
0
40
60
80
100
120
140
80
100
120
140
80
100
120
140
X Velocity [m/s]
T
Time
[sec]
1
0
-1
0
20
0
40
60
Y Velocity [m/s]
T
Time
[sec]
1
0
-1
0
20
0
40
60
T
Time
[sec]
Position [m]
15
10
5
0
0

105 SStarboard, 45
5 Port 1772
5
10
P
Position
[m]
15
GPS Yaw Rate [deg/sec]
20
0
-20
Unwrapped Heading [deg]
Velocity [m/s]
-40
0
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
2
1
0
0
500
0
-500
-1000
0
2
0
-2
0
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
5
0
-5
0
200
0
-200
0
Yaw Rate [rad/sec]
Yaw [deg]
Pitch [deg]
Roll [deg]
1
0
-1
0
173
10
Position [m]
8
6
4
2
0
0
2
4
6
Position [m]]
8
10
0

105 SStarboard, 55
5 Port 20
0
0
-20
0
-40
0
0
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
2
1
0
0
1000
0
0
-1000
0
-2000
0
0
1774
Roll [deg]
Pitch [deg]
0
-2
2
0
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
5
0
-5
5
0
200
0
0
-200
0
0
Yaw Rate [rad/sec]
Yaw [deg]
2
1
0
-1
0
10
Position [m]
8
6
4
2
0
0

105 SStarboard, 75
5 Port 1775
2
4
6
Position [m]
P
8
10
10
0
-10
-20
0
Unwrapped Heading [deg]
20
40
60
80
100
120
140
80
100
120
140
Time [sec]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
2
1
0
0
20
40
60
Time [sec]
500
0
-500
-1000
0
20
40
60
Time [sec]
80
100
120
Roll [deg]
5
0
-5
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
80
100
120
140
Pitch [deg]
Time [sec]
5
0
-5
0
20
40
60
200
0
-200
0
Yaw Rate [rad/sec]
Yaw [deg]
Time [sec]
20
40
60
Time [sec]
1
0
-1
0
20
40
60
Time [sec]
176
Position [m]
15
5
10
0
5
0
0
5
10
Position [m]
15
20

125 SStarboard, 45
5 Port Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
10
0
0
-10
0
-20
0
0
20
0
40
60
80
100
120
140
80
100
120
140
80
100
120
140
T
Time
[sec]
1.5
5
1
0.5
5
0
0
20
0
40
60
T
Time
[sec]
500
0
0
-500
0
-1000
0
0
20
0
40
60
T
Time
[sec]
1777
Roll [deg]
4
2
0
-2
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
Time [sec]
Pitch [deg]
2
0
-2
-4
0
20
40
60
Time [sec]
Yaw [deg]
200
0
-200
0
20
40
60
Time [sec]
Yaw Rate [rad/sec]
0.5
0
-0.5
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
X Velocity [m/s]
Time [sec]
1
0
-1
0
20
40
60
Y Velocity [m/s]
Time [sec]
1
0
-1
0
20
40
60
Time [sec]

125 Starboard, 55 Port 178
0
-50
0
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
50
10
20
30
40
Time [sec]
50
60
70
80
10
20
30
40
Time [sec]
50
60
70
80
10
20
30
40
Time [sec]
50
60
70
80
3
2
1
0
0
500
0
-500
-1000
0
2
0
-2
0
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
5
0
-5
0
200
0
-200
0
Yaw Rate [rad/sec]
Yaw [deg]
Pitch [deg]
Roll [deg]
1
0
-1
0
179
10
Position [m]
8
6
4
2
0
0
2
8
10
Velocity [m/s]
GPS Yaw Rate [deg/sec]
05 Port 125 SStarboard, 10
Unwrapped Heading [deg]

4
6
Pos
sition [m]
5
0
-5
5
-10
0
0
10
0
20
30
40
50
60
70
40
50
60
70
T
Time
[sec]
1.5
5
1
0.5
5
0
0
10
0
20
30
T
Time
[sec]
200
0
100
0
0
-100
0
0
10
20
30
40
Time [sec]
T
5
50
60
70
80
1 80
Roll [deg]
Pitch [deg]
Yaw Rate [rad/sec] Yaw [deg]
2
1
0
0
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
5
0
-5
5
0
100
0
0
-100
0
0
0.5
5
0
-0.5
5
0
Position [m]
15
10
5
0
0
5
Land Circle T
Tests: Right Tu
Turn 
35 Sttarboard, 55 P
Port 1 81
10
Positio
on [m]
15
GPS Yaw Rate [deg/sec]
Velocity [m/s]
Unwrapped Heading [deg]
5
0
-5
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
Time [sec]
1
0.5
0
0
20
40
60
Time [sec]
200
100
0
0
20
40
60
Time [sec]
Roll [deg]
5
0
-5
0
20
40
60
80
100
120
140
80
100
120
140
80
100
120
140
80
100
120
140
Pitch [deg]
Time [sec]
5
0
-5
0
20
40
60
Yaw Rate [rad/sec] Yaw [deg]
Time [sec]
0
-100
-200
0
20
40
60
Time [sec]
0.5
0
-0.5
0
20
40
60
Time [sec]
182
20
Position [m]
15
10
5
0
0
5

10
Position [m]
15
20
35 Sttarboard, 75 P
Port Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
20
0
10
0
0
-10
0
0
50
100
150
100
150
100
150
T
Time
[sec]
1
0.5
5
0
0
50
T
Time
[sec]
1000
0
500
0
0
0
50
T
Time
[sec]
1 83
Roll [deg]
2
0
-2
2
0
50
100
150
100
150
100
150
100
150
Pitch [deg]
T
Time
[sec]
5
0
-5
5
0
50
Yaw Rate [rad/sec] Yaw [deg]
T
Time
[sec]
200
0
0
-200
0
0
50
T
Time
[sec]
0.5
5
0
-0.5
5
0
50
T
Time
[sec]
12
Position [m]
10
8
6
4
2
0
0
2

45 Sttarboard, 75 P
Port 1 84
4
6
8
Position [m]
10
12
Motor Cmd
80
Port Cmd
76
75.5
40
30
75
20
60
30
40
50
60
70
80
74
10
0
10
20
30
40
50
60
70
80
40
30
60
20
50
40
10
0
10
20
30
40
0
0
10
20
30
40
50
60
70
80
50
60
70
80
0
90
400
200
GPS Yaw Rate [deg/sec]
Velocity [m/s]
0
90
80
70
Time [sec]
Unwrapped Heading [deg]
90
Current [amps]
20
74.5
Stbd Cmd
Track Force [N]
10
Current [amps]
40
0
90
Port
Starboard
10
5
0
-5
0
20
40
60
80
Time [sec]
100
120
140
160
20
40
60
80
Time [sec]
100
120
140
160
1.5
1
0.5
0
0
1000
500
0
0
50
100
150
Time [sec]
185
Roll [deg]
Pitch [deg]
Yaw Rate [rad/sec] Yaw [deg]
5
0
-5
5
0
20
40
60
80
Time [sec]
T
100
120
140
160
20
40
60
80
Time [sec]
T
100
120
140
160
20
40
60
80
Time [sec]
T
100
120
140
160
20
40
60
80
Time [sec]
T
100
120
140
160
5
0
-5
5
0
200
0
0
-200
0
0
0.5
5
0
-0.5
5
0
Position [m]
15
10
5
0
0
5

45 Sttarboard, 105
5 Port 1 86
10
Position
n [m]
15
20
0
0
-20
0
0
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
40
0
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
2
1
0
0
9
8
7
6
-1
-0.8
-0.6
-0.4
4
-0.2
0
Time [sec]
T
0.2
0.4
0.6
0.8
1
2
0
-2
2
0
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
20
40
60
Time [sec]
T
80
100
120
5
0
-5
5
0
200
0
0
-200
0
0
1
0
-1
0
12
10
Position [m]
Yaw Rate [rad/sec]
Yaw [deg]
Pitch [deg]
Roll [deg]
8
6
4
2
0
0
1 87
2
4
6
8
Position [m]
10
12
2

55 Starboard, 105 Port 20
10
0
-10
0
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
20
40
60
Time [sec]
80
100
120
2
1
0
0
500
0
0
Pitch [deg]
2
0
-2
0
5
0
-5
0
200
0
-200
0
Yaw Rate [rad/sec]
Yaw [deg]
20
1000
Roll [deg]
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
1
0
-1
0
188
Position [m]
15
5
10
0
5
0
0
5
10
Position [m]
1
15

75 Sttarboard, 105
5 Port 10
0
5
0
-5
5
0
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
2
1
0
0
200
0
150
0
100
0
50
0
0
1 89
Roll [deg]
Pitch [deg]
Yaw Rate [rad/sec] Yaw [deg]
2
0
-2
2
0
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
10
20
30
40
Time [sec]
T
5
50
60
70
80
5
0
-5
5
0
200
0
0
-200
0
0
0.5
5
0
-0.5
5
0
20
Position [m]
15
10
5
0
0

45 Sttarboard, 125
5 Port 1990
5
10
Po
osition [m]
15
20
20
0
0
-20
0
0
Unwrapped Heading [deg]
10
20
30
40
50
60
70
80
90
50
60
70
80
90
50
60
70
80
90
T
Time
[sec]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
40
0
2
1
0
0
10
20
30
40
T
Time
[sec]
1500
0
1000
0
500
0
0
0
10
20
30
40
T
Time
[sec]
5
0
-5
5
0
10
20
30
0
40
50
Time [sec]
T
60
70
80
90
100
10
20
30
0
40
50
Time [sec]
T
60
70
80
90
100
10
20
30
0
40
50
Time [sec]
T
60
70
80
90
100
10
20
30
0
40
50
Time [sec]
T
60
70
80
90
100
5
0
-5
5
0
200
0
0
-200
0
0
1
0
-1
0
8
6
Position [m]
Yaw Rate [rad/sec]
Yaw [deg]
Pitch [deg]
Roll [deg]
4
2
0
0
1991
2
4
Position [m]
6
8

55 Starboard, 125 Port 20
0
-20
-40
0
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
2
1
0
0
500
0
-500
-1000
0
2
0
-2
0
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
10
20
30
Time [sec]
40
50
60
5
0
-5
0
200
0
-200
0
Yaw Rate [rad/sec]
Yaw [deg]
Pitch [deg]
Roll [deg]
1
0
-1
0
192
8
Position [m]
6
4
2
0
0
2

4
Position [m]
6
8
25 Port 105 SStarboard, 12
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
5
0
-5
5
-10
0
0
10
0
20
30
40
50
60
70
40
50
60
70
T
Time
[sec]
1.5
5
1
0.5
5
0
0
10
0
20
30
T
Time
[sec]
200
0
100
0
0
-100
0
0
10
20
30
40
Time [sec]
T
5
50
60
70
80
1993
Roll [deg]
26.055
5
26.055
5
26.055
5
0
5
10
15
20
25
15
20
25
15
20
25
15
20
25
Pitch [deg]
T
Time
[sec]
-80.1126
6
-80.1126
6
-80.1126
6
-80.1126
6
0
5
10
Yaw Rate [rad/sec] Yaw [deg]
T
Time
[sec]
-18
8
-20
0
-22
2
0
5
10
T
Time
[sec]
10
0
0
-10
0
0
5
10
T
Time
[sec]
Position [m]
15
10
5
0
0
5
Water Tests:: Left Turn 
80 Sttarboard, 0 Po
ort 1994
10
Po
osition [m]
15
GPS Yaw Rate [deg/sec]
Velocity [m/s]
Unwrapped Heading [deg]
10
0
0
-10
0
0
50
100
150
200
250
T
Time
[sec]
300
35
50
400
450
50
100
150
200
250
T
Time
[sec]
300
35
50
400
450
50
100
150
200
250
T
Time
[sec]
300
35
50
400
450
1.5
5
1
0.5
5
0
0
500
0
0
-500
0
-1000
0
0
60
Position
os o [[m]]
50
40
30
20
10
0
0

100 SStarboard, 0 P
Port 1995
20
40
Position [m]
60
GPS Yaw Rate [deg/sec]
Velocity [m/s]
Unwrapped Heading [deg]
20
10
0
-10
0
50
100
150
200
250
Time [sec]
300
350
400
450
500
50
100
150
200
250
Time [sec]
300
350
400
450
500
50
100
150
200
250
Time [sec]
300
350
400
450
500
1.5
1
0.5
0
0
200
0
-200
-400
0
10
0
-10
0
Yaw Rate [rad/sec] Yaw [deg]
Pitch [deg]
Roll [deg]
50
100
150
200
250
Time [sec]
300
350
400
450
500
50
100
150
200
250
Time [sec]
300
350
400
450
500
50
100
150
200
250
Time [sec]
300
350
400
450
500
50
100
150
200
250
Time [sec]
300
350
400
450
500
5
0
-5
0
200
0
-200
0
0.5
0
-0.5
0
196
60
Position [m]
50
40
30
20
10
0
0

100 SStarboard, ‐40 Port 1997
20
40
P
Position
[m]
60
GPS Yaw Rate [deg/sec]
Velocity [m/s]
0
-10
0
-20
0
0
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
1.5
5
1
0.5
5
0
0
500
0
0
-500
0
-1000
0
0
10
0
0
-10
0
0
5
0
-5
5
0
200
0
0
-200
0
0
0.5
5
0
-0.5
5
0
70
60
Position [m]
Yaw Rate [rad/sec] Yaw [deg]
Pitch [deg]
Roll [deg]
Unwrapped Heading [deg]
10
0
50
40
30
20
10
0
0
20
1998
40
Posiition [m]
60

100 Starboard, ‐80 Port 10
0
-10
-20
0
50
100
150
200
250
300
350
200
250
300
350
200
250
300
350
200
250
300
350
200
250
300
350
200
250
300
350
200
250
300
350
Time [sec]
1.5
1
0.5
0
0
50
100
150
Time [sec]
500
0
-500
-1000
0
50
100
150
Time [sec]
Roll [deg]
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
10
0
-10
0
50
100
150
Pitch [deg]
Time [sec]
5
0
-5
0
50
100
150
Yaw Rate [rad/sec] Yaw [deg]
Time [sec]
200
0
-200
0
50
100
150
Time [sec]
0.5
0
-0.5
0
50
100
150
Time [sec]
199
P iti [[m]]
Position
40
30
20
10
0
0
10

20
30
Positio
on [m]
40
100 SStarboard, ‐100 Port Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
10
0
0
-10
0
-20
0
0
50
0
100
150
200
250
300
350
200
250
300
350
200
250
300
350
T
Time
[sec]
1.5
5
1
0.5
5
0
0
50
0
100
150
T
Time
[sec]
1000
0
0
-1000
0
-2000
0
0
50
0
100
150
T
Time
[sec]
2000
Roll [deg]
10
0
0
-10
0
0
50
0
100
150
200
250
300
350
200
250
300
350
200
250
300
350
200
250
300
350
Pitch [deg]
T
Time
[sec]
5
0
-5
5
0
50
0
100
150
Yaw Rate [rad/sec] Yaw [deg]
T
Time
[sec]
200
0
0
-200
0
0
50
0
100
150
T
Time
[sec]
0.5
5
0
-0.5
5
0
50
0
100
150
T
Time
[sec]
4
40
Position [m]
3
30
2
20
10
0
0

125 SStarboard, 0 P
Port 2001
10
20
Position [m]
3
30
40
GPS Yaw Rate [deg/sec]
Velocity [m/s]
0
-10
0
0
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
50
100
150
200
Time [sec]
T
2
250
300
350
400
1.5
5
1
0.5
5
0
0
500
0
0
-500
0
-1000
0
0
10
0
0
-10
0
0
Yaw Rate [rad/sec] Yaw [deg]
Pitch [deg]
Roll [deg]
Unwrapped Heading [deg]
10
0
2
0
-2
2
0
200
0
0
-200
0
0
0.2
2
0
-0.2
2
0
6
60
Position [m]
5
50
4
40
3
30
2
20
1
10
0
0
2002
20
0
40
Position [m]
60
Unwrapped Heading [deg]
Velocity [m/s]
GPS Yaw Rate [deg/sec]
125 Starboard, ‐45 Port 10
0
-10
0
50
100
150
200
250
Time [sec]
300
350
400
450
50
100
150
200
250
Time [sec]
300
350
400
450
50
100
150
200
250
Time [sec]
300
350
400
450
1.5
1
0.5
0
0
500
0
-500
-1000
0
10
0
-10
0
Pitch [deg]
Roll [deg]
Yaw Rate [rad/sec] Yaw [deg]

50
100
150
200
250
Time [sec]
300
350
400
450
50
100
150
200
250
Time [sec]
300
350
400
450
50
100
150
200
250
Time [sec]
300
350
400
450
50
100
150
200
250
Time [sec]
300
350
400
450
2
0
-2
0
200
0
-200
0
0.5
0
-0.5
0
203
50
Position [m]
40
30
20
10
0
0

125 SStarboard, ‐125 Port 2004
10
20
30
40
Po
osition [m]
50
GPS Yaw Rate [deg/sec]
Velocity [m/s]
0
-10
0
-20
0
0
50
100
150
200
250
150
200
250
150
200
250
150
200
250
150
200
250
150
200
250
150
200
250
T
Time
[sec]
1.5
5
1
0.5
5
0
0
50
100
T
Time
[sec]
500
0
0
-500
0
-1000
0
0
50
100
T
Time
[sec]
Roll [deg]
Unwrapped Heading [deg]
10
0
10
0
0
-10
0
0
50
100
Pitch [deg]
T
Time
[sec]
2
0
-2
2
0
50
100
Yaw Rate [rad/sec] Yaw [deg]
T
Time
[sec]
200
0
0
-200
0
0
50
100
T
Time
[sec]
0.5
5
0
-0.5
5
0
50
100
T
Time
[sec]
35
Position [m]
30
25
20
15
10
5
0
0
2005
10
2
20
Position [m]
30
B. Matlab Code OS5000 Compass clear all
close all
clc
%
%
%
%
%
%
%
%
%
Joe Marquardt DUKW-ling. PARSE OS5000 compass data
DATA MUST BE IN THE FOLLOWING FORMAT:
NOW THAT IT IS IN 24 HOUR CLOCK
"3/16/2012 15:36:42",$C223.0P-1.2R-0.5T31.6*24
This code reads in compass data (saved in the directory as a .dat
file) from the OS5000 digital compass. It plots heading,
roll angle and pitch angle vs. time.
Time is Coordinated Universal Time (UTC), synchronized on data
collection computer so timestamp matches other data
%% Open Compass Data File (Make sure first line is Data)
% Use textscan to parse data (time,heading, roll and pitch)
compass = fopen('compass.dat');
compass_data = textscan(compass,
'%s%f%c%f%c%f%c%c%c%c%f%c%f%c%f%c%f%c%f%s');
fclose(compass);
%% Define the columns of data needed for plotting
hour_cell = compass_data(:,2);
hour = cell2mat(hour_cell);
minute_cell = compass_data(:,4);
minute = cell2mat(minute_cell);
second_cell = compass_data(:,6);
second = cell2mat(second_cell);
hours_in_sec = hour.*3600;
minutes_in_sec = minute.*60;
UTC_time_in_sec = hours_in_sec + minutes_in_sec + second;
heading_degrees = compass_data{11};
pitch_angle = compass_data{13};
roll_angle = compass_data{15};
% Plot Data
% Subtract MIN so plot starts at zero
UTC_time_in_sec = UTC_time_in_sec - min(UTC_time_in_sec);
% Plot Heading in Degrees vs. UTC Time
plot(UTC_time_in_sec,heading_degrees)
xlabel('Time [sec]')
ylabel('Heading [deg]')
set(get(gca,'Xlabel'),'FontSize',14)
set(get(gca,'Ylabel'),'FontSize',14)
set(gca,'FontSize',14);
206
figure
% Plot Pitch Angle in Degrees vs. Time
plot(UTC_time_in_sec,pitch_angle)
xlabel('Time [sec]')
ylabel('Pitch [deg]')
set(get(gca,'Xlabel'),'FontSize',14)
set(get(gca,'Ylabel'),'FontSize',14)
set(gca,'FontSize',14);
figure
% Plot Roll Angle in Degrees vs. Time
plot(UTC_time_in_sec,roll_angle)
xlabel('Time [sec]')
ylabel('Roll [deg]')
set(get(gca,'Xlabel'),'FontSize',14)
set(get(gca,'Ylabel'),'FontSize',14)
set(gca,'FontSize',14);
C. Vision System Development Vision Based Navigation Background
Vision based navigation is popular among autonomous vehicles that operate on land and sea. It
provides a relatively inexpensive means of obstacle avoidance when compared to LIDAR
systems. Stereo vision, which provides the vehicle with a 3D depth perception of its
surroundings, can also replace the need for complex LIDAR systems in some cases. Another
option is to combine the use of LIDAR and stereovision for more accurate results.
Stereo vision allows a control system to understand its surroundings better than monocular
vision because it provides depth perception. There are many autonomous systems that use stereo
vision as a means of obstacle avoidance. In [42], an autonomous car uses stereo vision cameras
to navigate roads while avoiding obstacles such as pedestrians and other vehicles. This is the
only form of obstacle detection used on the vehicle and proves to be an efficient means of
navigation.
Light detection and ranging (LIDAR) systems are another technique for obstacle detection and
navigation. These systems are complex and expensive, and in the open water environment the
vehicle will primarily be located in, it may not be needed. LIDAR also has a disadvantage in
that, although it has good range and resolution, it only is capable of scanning a single plane. For
example, if one object in the field of view is blocked by another, it is not detected by the
LIDAR system.
207
In [33], testing showed that a 33 cm baseline stereo vision camera system performed well in
short range, but when compared to a LIDAR system in long range experiments, its accuracy
was not comparable. This project, a seven mile, autonomous high speed dessert race, required
accurate long range obstacle sensing, because of the speeds the vehicle was traveling. Because
of this, they discontinued the development of the stereo system based on its long range
limitations. [33] also suggests a wider baseline between the cameras could have increased the
range capabilities of the stereo vision system but was not tested because of the positive results
of the LIDAR system.
Coupling a LIDAR device with stereo vision would combine the 3D sensing of stereo vision
with the accuracy of LIDAR, giving a precise 3D representation of the vehicle’s surroundings
[22]. Stereo vision has limitations with longer range targets, as well as computational errors. It
does, however, provide a vehicle with enough information for semi-complex navigation
procedures [41]. Coupling the two systems, as outlined in the slam documentation allows for a
process called Simultaneous Localization and Mapping, or SLAM. SLAM is a process where an
autonomous vehicle can create a 3D point cloud, or 3D map of its surroundings, while
simultaneously updating its current location within the map. This procedure could be beneficial
for the DUKW-21 concept in its amphibious mission.
OpenCV is an open source library of image processing software. There are currently over 500
functions available through this software. The development of this software was started by Intel
in 1999 [2]. Using OpenCV for autonomous vehicle navigation is a popular application of this
open source software.
OpenCV libraries include toolboxes that allow blob tracking, edge and pattern recognition and
color recognition. These functions are important for navigation and control of an autonomous
vehicle. Using these library functions in OpenCV will allow for rapid development of an
obstacle avoidance system in this project. For example, [19] uses optical flow and corner
recognition algorithms in OpenCV for the control of an autonomous vehicle. This method uses
apparent motion of an object based on the relative motion of the vehicle and its surroundings.
This method would be applicable to our vehicle as it quickly navigates through the surf zone,
since the motion of the vehicle and potential obstacles will be changing very quickly in the
region. The work outlined in [3] uses optical flow techniques to track obstacles in real time for
use in autonomous control of a small car. These experiments were successful in tracking fast
moving Stereo Vision Camera System
208
There are several methods of autonomous obstacle avoidance and navigation. Systems such as
LIDAR, ultrasonic range sensors, infrared proximity sensors, monocular cameras and stereo
vision cameras are systems that are used for autonomous navigation. This project will explore
the use of a stereo vision system to perform the task of locating obstacles. Stereo vision imitates
the technique a human uses to detect the range of an object in front of him. By matching the
images from the left and right eyes, which are at a known distance apart from each other, the
human brain can determine the location and distance of what it sees. Similarly, a stereo vision
camera system determines the distance a potential obstacle is away from the vehicle, and relays
this information to the control system for avoidance.
Cameras
Knowing the exact distance between the two cameras is necessary for range calculations. A
closer baseline will provide better accuracy of detecting obstacles at close range because of the
reduced blind spot that will occur. However, a wide baseline system will allow better resolution
of long range obstacles [25].
While there are “off-the-shelf” stereo cameras on the market for autonomous vehicles, the
project will explore the use of a simple webcam based system. The vehicle is required to locate
navigation buoys and obstacles no less than one foot in diameter within two vehicle lengths.
Given these requirements; a webcam’s range, resolution and processing rate allow it to perform
this task sufficiently. Webcams are an inexpensive way to explore the capabilities of stereo
vision as a means of obstacle avoidance for an amphibious vehicle. The inexpensive cameras
also allow the opportunity to explore the use of a multi-stereo camera system, with wide
baseline cameras coupled with small baseline, short range cameras.
For initial testing, a Minoru 3D webcam, shown in the figure below was used. This web cam is
designed to perform three dimensional representations of the images it captures. The system is
simply two webcams that share a USB port. These cameras will serve as a simple way to
explore the application of stereo vision on the DUKW-ling. The Minoru web cam will be
enclosed in a waterproof housing and mounted to the top of the vehicle. Initial testing will
determine the capabilities of the camera’s use for autonomous stereo vision, as well as the need
for a second wider-baseline system. These cameras are powered through the USB cable, and
therefore require minimal electrical complexity.
209
The stereo viision camera system
s
will provide
p
the coontrol system will informattion about thee
vehicle’s surrroundings. It will utilize itts own image processing coomputer, passsing necessarry
information to
t the control system using
g serial comm
munication. Thhis separate ccomputer was
chosen to allo
ow image pro
ocessing, one of the most ccomputationally demandinng sensor
processing taasks, to be sep
parate from th
he main contrrol computer. This will alloow faster upddates
of understand
ding the vehiccle’s surround
dings while nnot slowing doown the otherr tasks requireed for
autonomous control. The vision
v
compu
uter will be a W
Windows bassed imbeddedd processor,
because using
g OpenCV is more simpliffied on this tyype of processsor. The mainn control com
mputer
will request information
i
from
fr
the vision
n computer too initiate this function in thhe camera
software. Forr example, wh
hen the vehicle is navigatinng offshore, tthe control coomputer can
request the lo
ocation of nav
vigation aids (buoys, channnel markers), as well as pootential obstaccles
along the cou
urse. When th
he vehicle is on
o land, a preddetermined path on the beach can be
followed by line
l tracking, where the caamera computter will relay the path to thhe control
computer forr navigation.
OpenCV
The stereo viision system will
w be develo
oped using thhe Open Sourcce Computer Vision (OpennCV)
library. Open
nCV is a free library of com
mputer visionn infrastructurre that aids inn the developm
ment
of vision app
plications. Altternatives to OpenCV
O
are tthe Gandalf vvision library, EmbedCV annd
Blepo. With over 500 funcctions, OpenC
CV software aallows faster developmentt of vision bassed
h as stereo vission obstacle avoidance [22]. The docum
mentation andd references onn
systems, such
OpenCV, as well as many
y past projectss that have utiilized OpenCV make it an ideal choice for
applying to th
his project wh
hen compared
d to other lesss popular librraries.
Stereo vision
n is a computeer emulation of
o the depth pperception givven to us by oour eyes. A
computer acccomplishes th
his task by maatching similaarities betweeen two imagess from cameraas at
a known distance apart (caamera base-liine). Using geeometry, the ddistance of thhe object deteccted
2 10
can be determ
mined. OpenC
CV contains many
m
functionns unique to sstereo vision, and can be used
to perform th
he process of stereo vision::
Un-distortio
on – Radial an
nd tangential lens distortionn is removed mathematicaally.
Rectification
n – Adjust forr the angles an
nd base-line, which gives an output of iimages that are
row-aligned and
a rectified. Row aligned
d means the im
mages are copplanar, and arre exactly aliggned
with one another.
Correspondence – Find similar
s
featurees between thhe left and rigght camera im
mages. The output
of this processs is a “disparrity map.” A disparity
d
mapp is a matrix tthat defines thhe difference in xcoordinates of
o the similar feature vieweed in each cam
mera Xdisparity = Xleft-Xright
Triangulatio
on and Repro
ojection – Ussing the know
wn baseline seeparation of thhe cameras, thhe
disparity map
p can be conv
verted to distaances and now
w a “depth maap” of what thhe cameras seee can
be defined [2
2].
The figure ab
bove explainss the procedurre of computeer based stereo vision [2]. O
OpenCV contains
library functiions that perfo
form these callculations, as well as more advanced callculations thaat will
help locate potential obstaacles and defin
ne the vehiclee’s surroundinngs. The ability of locatingg
a the shore lin
ne, incoming waves and innclines will allso be exploreed. This will bbe
things such as
done by recording video on
o the vehiclee during remoote control opeeration. This video will theen be
used to test different
d
functtions and algo
orithms to dettermine the best way of loccating these
objects on a laptop,
l
wheree bench-style testing can exxpedite this pprocess. OpennCV also has
functions thaat determine th
he location off an object off known dimeensions or patttern, which can be
applied to container paylo
oad localizatio
on.
2 11
The four main functions that will be performed by the stereo vision system will be: blob
tracking, line tracking and shape and pattern recognition. Blob tracking will be a means of
obstacle avoidance for the vehicle. It will notify the control system of objects in front of the
vehicle to be avoided. Line tracking could identify the shoreline, and be used to guide the
vehicle along a path once on land. Shape and pattern recognition can be used for offshore
navigation to recognize channel markers and navigation buoys.
Vision System Development
The vision system software was developed using the tools in the OpenCV library. The focus of
software development was blob tracking, the most beneficial tool for navigating through the
surf zone onto the beach.
The first vision code developed identifies circular objects of a defined range of colors. This
range of colors is defined using HSV (hue, saturation and value) color space. This color space is
less susceptible to sunlight. The user can define a color or a range of colors and define this as
the “range of interest” within the developed software. When the software is used, it places a
circle around the area that contains the most pixels of the defined range of interest. The
software’s output is the radius of the circle and its position in the camera frame. This code can
be used to identify navigational buoys and their distance away from the vehicle can be
determined by the radius of the bounding circle. The results of testing will be detailed in section
3.2.
The second vision code developed identifies multiple blobs and outputs their location. This code
defines regions of the defined color range by enclosing the areas in a rectangle. The area of each
rectangle found and the rectangles’ centroids are given. This code can be used in avoiding
obstacles as well as navigating through buoys. Testing results are detailed in section 3.2.
Other functions that have been initially developed are SIFT and SURF template matching,
stereo vision, line/edge tracking and motion tracking.
212
Vision Systeem
The vision sy
ystem softwarre that was deeveloped for tthis vehicle has only been tested in bencchtop style testss. Because the vehicle is not
n yet autonoomous, it was not used for navigation orr
obstacle avoiidance in the test zone as of
o this report w
writing. Plannned research iin the followiing
year of this project
p
will uttilize the deveeloped vision system softw
ware as a meanns of obstaclee
avoidance an
nd navigation.. The aim of this
t software developmentt was to accurrately identifyy
objects in thee path of the vehicle
v
for naavigation and obstacle avoiidance. The vvision system can
also be used for locating th
he payload co
ontainer to peerform its autoonomous carggo transfer
mission. Thee container waas placed at different distannces from thee cameras, andd its size and
location in th
he camera fram
me was recorrded and comppared to actuaal position.
Besides locatting potential obstacles, the most obviouus requiremennt of the visioon system waas to
locate a chan
nnel for the veehicle to navig
gate through. To test this ffunctionality, conventionall red
and green bu
uoys were used for channell markers, andd the softwaree was tested ooutdoors to giive
2 13
the position and size of these buoys. The measured size of the buoys can be used to determine
their distance from the vehicle if the channel markers in future testing are a uniform size. This
will be detailed in the results section.
Testing was performed in different lighting conditions, to determine any limitations of the
cameras.
Some Current Results
The four main functions the camera system will be responsible for are blob tracking, line
tracking and shape and pattern recognition. Blob and line tracking apply to obstacle avoidance,
since the camera will be able to locate objects in the frames and define the location of these
objects. If the X and Y axes point to the left and up, respectively, the Z axis will point straight
out in front of the vehicle. The X and Y location will define the angle at which the object is
detected, and the Z location will be its distance from the vehicle. Distance estimates are
performed by stereo vision, comparing disparities between the two cameras.
Currently, OpenCV has been used to locate a circle of a user defined color, and output the X
and Y location of the centroid of the circle within the image frame. The program uses a video
stream from one camera, converts the image from RGB to the HSV color space, which
represents hue, saturation and brightness of the color. It was found from previous computer
vision projects that filtering colors is easier in the HSV color space [42]. The colors outside of
the defined range are then filtered out. A Hough transform defines the circle seen in the image.
A Hough transform estimates a circular region surrounding the isolated pixels (in this case all
red pixels). A circle is overlaid around the circle detected in the frame by the Hough transform.
The output is the X and Y coordinate of the circle’s center, and an estimate of its radius. This
process can be seen below.
214
f
the OpenCV soft
ftware can perrform. Trackinng
This demonstrates one of the possible functions
ne object is more
m
useful wh
hen navigatinng, and the figgure below shhows how the
more than on
camera can detect
d
multiple blobs and number
n
each oobject it deteccts. This function would bee
ideal for naviigating throug
gh buoys or detecting
d
know
wn objects inn the vehicle’ss path. The sizze of
the objects deetected and th
heir location in
i the frame aand in relationn to each otheer is the next step
in this particu
ular blob tracker developm
ment.
2 15
The next step
p is stereo vision, using both cameras foor depth calcuulations. As ooutlined abovee,
determining the
t Z location
n of objects detected
d
by steereo vision is a four step pprocess. Theree are
specific stereeo vision funcctions in Open
nCV that allo w filtering, reectification, ddisparity maps and
depth calculaations.
D. SolidWorks CAD Drawings Wh
heel Axle Dropp Bracket Spro
ocket Axle Droop Bracket 2 16
Maain Drivetrain Housing Axle Beariing 2 17
Drivetrain Asseembled Sprocket A
Axle 2 18
6
REFERE
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P.. Bon, A. An
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ow Waters Using
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Spread-Spectrum Signaling aand a Tetrahhedrial Ultraashort
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Vol. 44 #5, 22010.
[2] Bradski,
B
G. and Kaehller, A., Leaarning OpennCV. Sabastopol, CA, U
USA:
O’Reilly Meedia, 2008.
[3] Braillon, C.
C Pradalier, C. Crowleey, J. Lauggier, C. “Reeal-time Mooving
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[4] Corradini,
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M.
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C
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Measuremennt in a
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D. Stenz, A. “Using
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ournal of Fieeld Roboticss, Volume 233, 2006.
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[8] Flom, B. “DUKW 21 Autonomous Navigation – Autonomous Path Planning
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[11] Furfaro, T., “Path-Following Control of the Wave Adaptive Modular
Vessel,” Florida Atlantic University, Dania Beach, FL, USA, MS Thesis (in progress),
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[12] Gilmore, T. and Johnson, B. Introduction to Naval Architecture, Annapolis,
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[13] Gonzales, F. Orme, R. Ruppert, A. and Schaffer, J. “DUKW 21 –
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