Intelligent Autonomous Robotics: A Robot Soccer Case Study (Synthesis Lectures on Artificial Intelligence and Machine Learning)

166 Pages·2007·1.55 MB·English

by  Peter Stone

MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
Intelligent Autonomous Robotics
A Robot Soccer Case Study
i
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
ii
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
iii
Synthesis Lectures on Artificial
Intelligence and Machine Learning
Editors
RonaldJ.Brachman,YahooResearch
TomDietterich,OregonStateUniversity
IntelligentAutonomousRobotics
PeterStone
2007
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
Copyright© 2007byMorgan&Claypool
Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedin
anyformorbyanymeans—electronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotations
inprintedreviews,withoutthepriorpermissionofthepublisher.
IntelligentAutonomousRobotics
PeterStone,TheUniversityofTexasatAustin
www.morganclaypool.com
ISBN:1598291262 paperback
ISBN:9781598291261 paperback
ISBN:1598291270 ebook
ISBN:9781598291278 ebook
DOI:10.2200/S00090ED1V01Y200705AIM001
APublicationintheMorgan&ClaypoolPublishers’series
SYNTHESISLECTURESONARTIFICIALINTELLIGENCEANDMACHINELEARNING#1
Lecture#1
SeriesEditors:RonaldBrachman,Yahoo!ResearchandThomasG.Dietterich,OregonStateUniversity
FirstEdition
10987654321
iv
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
Intelligent Autonomous Robotics
A Robot Soccer Case Study
PeterStone
TheUniversityofTexasatAustin
SYNTHESISLECTURESONARTIFICIALINTELLIGENCEANDMACHINE
LEARNING#1
M
&C &
M o r g a n C l a y p o o l P u b l i s h e r s
v
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
vi
ABSTRACT
Roboticstechnologyhasrecentlyadvancedtothepointofbeingwidelyaccessibleforrelatively
low-budget research, as well as for graduate, undergraduate, and even secondary and primary
school education. This lecture provides an example of how to productively use a cutting-edge
advancedroboticsplatformforeducationandresearchbyprovidingadetailedcasestudywith
the Sony AIBO robot, a vision-based legged robot. The case study used for this lecture is the
UT Austin Villa RoboCup Four-Legged Team. This lecture describes both the development
process and the technical details of its end result. The main contributions of this lecture are
(i)aroadmapfornewclassesandresearchgroupsinterestedinintelligentautonomousrobotics
who are starting from scratch with a new robot, and (ii) documentation of the algorithms
behind our own approach on the AIBOs with the goal of making them accessible for use on
othervision-basedand/orleggedrobotplatforms.
KEYWORDS
Autonomousrobots,Leggedrobots,Multi-RobotSystems,Educationalrobotics,Robotsoccer,
RoboCup
ACKNOWLEDGMENT
This lecture is based on the work and writing of many people, all from the UT Austin Villa
RoboCup team. A significant amount of material is from our team technical report written
afterthe2003 RoboCupcompetitionandwrittenincollaborationwithKurtDresner, SelimT.
ErdoErdog˘an,PeggyFidelman,NicholasK.Jong,NateKohl, GregoryKuhlmann,EllieLin,
MohanSridharan,DanielStronger,and GurushyamHariharan[78].Somematerialfrom the
team’s2004,2005,and2006technicalreports,co-authoredwitha subsetoftheabovepeople
plus Tekin Meric¸li and Shao-en Yu, is also included [79, 80, 81]. This research is supported
in part by NSF CAREER award IIS-0237699, ONR YIP award N00014-04-1-0545, and
DARPA grantHR0011-04-1-0035.
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
vii
Contents
1. Introduction..................................................................1
2. TheClass.....................................................................5
3. InitialBehaviors...............................................................7
4. Vision........................................................................9
4.1 CameraSettings ........................................................ 10
4.2 ColorSegmentation.....................................................11
4.3 RegionBuildingandMerging............................................15
4.4 ObjectRecognitionwithBoundingBoxes.................................17
4.5 PositionandBearingofObjects .......................................... 22
4.6 VisualOpponentModeling..............................................23
5. Movement...................................................................27
5.1 Walking................................................................27
5.1.1 Basics...........................................................27
5.1.2 ForwardKinematics..............................................28
5.1.3 InverseKinematics...............................................29
5.1.4 GeneralWalkingStructure.......................................32
5.1.5 OmnidirectionalControl.........................................33
5.1.6 TiltingtheBodyForward.........................................35
5.1.7 TuningtheParameters...........................................36
5.1.8 OdometryCalibration............................................36
5.2 GeneralMovement......................................................37
5.2.1 MovementModule..............................................37
5.2.2 MovementInterface ............................................. 40
5.2.3 High-LevelControl..............................................43
5.3 LearningMovementTasks...............................................44
5.3.1 ForwardGait....................................................44
5.3.2 BallAcquisition ................................................. 45
6. FallDetection................................................................47
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
viii INTELLIGENTAUTONOMOUSROBOTICS
7. Kicking......................................................................49
7.1 CreatingtheCriticalAction..............................................50
7.2 IntegratingtheCriticalActionintotheWalk..............................51
8. Localization.................................................................53
8.1 Background.............................................................54
8.1.1 BasicMonteCarloLocalization...................................55
8.1.2 MCLforVision-BasedLeggedRobots............................56
8.2 EnhancementstotheBasicApproach.....................................57
8.2.1 LandmarkHistories..............................................57
8.2.2 Distance-BasedUpdates..........................................59
8.2.3 ExtendedMotionModel.........................................59
8.3 ExperimentalSetupandResults..........................................60
8.3.1 Simulator.......................................................60
8.3.2 ExperimentalMethodology.......................................60
8.3.3 TestforAccuracyandTime ...................................... 61
8.3.4 TestforStability.................................................63
8.3.5 ExtendedMotionModel.........................................64
8.3.6 Recovery........................................................65
8.4 LocalizationSummary...................................................66
9. Communication..............................................................69
9.1 InitialRobot-to-RobotCommunication...................................69
9.2 MessageTypes..........................................................70
9.3 KnowingWhichRobotsAreCommunicating..............................70
9.4 DeterminingWhenATeammateIs“Dead”...............................71
9.5 PracticalResults.........................................................71
10. GeneralArchitecture.........................................................73
11. GlobalMap..................................................................75
11.1 MaintainingLocationData..............................................75
11.2 InformationfromTeammates............................................76
11.3 ProvidingaHigh-LevelInterface.........................................78
12. Behaviors....................................................................79
12.1 GoalScoring ........................................................... 79
12.1.1 InitialSolution..................................................79
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
CONTENTS ix
12.1.2 IncorporatingLocalization........................................80
12.1.3 AFiniteStateMachine .......................................... 82
12.2 Goalie ................................................................. 84
13. Coordination................................................................87
13.1 Dibs...................................................................87
13.1.1 RelevantData...................................................87
13.1.2 Thrashing.......................................................87
13.1.3 Stabilization.....................................................88
13.1.4 TakingtheAverage..............................................88
13.1.5 Aging .......................................................... 88
13.1.6 CallingtheBall..................................................88
13.1.7 SupportDistance................................................89
13.1.8 PhasingoutDibs................................................89
13.2 FinalStrategy...........................................................89
13.2.1 Roles...........................................................89
13.2.2 SupporterBehavior .............................................. 90
13.2.3 DefenderBehavior...............................................91
13.2.4 DynamicRoleAssignment ....................................... 92
14. Simulator....................................................................95
14.1 BasicArchitecture.......................................................95
14.2 ServerMessages.........................................................95
14.3 SensorModel...........................................................96
14.4 MotionModel..........................................................96
14.5 GraphicalInterface......................................................96
15. UTAssist....................................................................99
15.1 GeneralArchitecture....................................................99
15.2 DebuggingData.......................................................100
15.2.1 VisualOutput..................................................100
15.2.2 LocalizationOutput............................................101
15.2.3 MiscellaneousOutput...........................................102
15.3 VisionCalibration......................................................102
16. Conclusion.................................................................105
A. HeuristicsfortheVisionModule.............................................107
A.1 RegionMergingandPruningParameters.................................107
MOBK082-FM MOBK082-Stones.cls June29,2007 9:7
x INTELLIGENTAUTONOMOUSROBOTICS
A.2 Tilt-AngleTest........................................................108
A.3 CircleMethod.........................................................109
A.4 BeaconParameters.....................................................111
A.5 GoalParameters.......................................................113
A.6 BallParameters........................................................114
A.7 OpponentDetectionParameters.........................................114
A.8 OpponentBlobLikelihoodCalculation..................................115
A.9 CoordinateTransforms.................................................115
A.9.1 WalkingParameters............................................116
B. Kicks.......................................................................119
B.1 InitialKick............................................................119
B.2 HeadKick.............................................................119
B.3 Chest-PushKick.......................................................120
B.4 ArmsTogetherKick ................................................... 121
B.5 Fall-ForwardKick ..................................................... 121
B.6 BackKick.............................................................123
C. TCPGateway...............................................................125
D. ExtensiontoWorldStatein2004.............................................127
E. SimulatorMessageGrammar................................................131
E.1 ClientActionMessages.................................................132
E.2 ClientInfoMessages...................................................132
E.3 SimulatedSensationMessages...........................................132
E.4 SimulatedObservationMessages........................................133
F. CompetitionResults........................................................135
F.1 AmericanOpen2003...................................................135
F.2 RoboCup2003 ........................................................ 137
F.3 ChallengeEvents2003.................................................140
F.4 U.S.Open2004 ....................................................... 141
F.5 RoboCup2004 ........................................................ 143
F.6 U.S.Open2005 ....................................................... 144
F.7 RoboCup2005 ........................................................ 145
References..................................................................147
Biography..................................................................155