The Incremental Development of a Synthetic Multi-Agent System: The UvA Trilcarn 2001 Robotic Soccer Simulation Team

217 Pages·2002·1.68 MB·English

by  Boer B., Kok J.

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Tt he Incremental Development of a
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U2 vA Trilearn 2001 Robotic Soccer
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Master’s thesis for Artiflt+c1ial Intelligence and Computer Science
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Faculty of Science
University of Amsterdam

Abstract
This thesis describes the incremental development and main features of a synthetic multi-agent system
called UvA Trilearn 2001. UvA Trilearn 2001 is a robotic soccer simulation team that consists of eleven
autonomous software agents. Itoperatesinaphysicalsoccersimulation systemcalledsoccerserverwhich
enablesteamsofautonomoussoftwareagentstoplayagameofsocceragainsteachother. Thesoccerserver
provides a fully distributed and real-time multi-agent environment in which teammates have to cooperate
to achieve their common goal of winning the game. The simulation models many real-world complexities
such as noise in object movement, noisy sensors and actuators, limited physical abilities and restricted
communication. This thesis addresses the various components that make up the UvA Trilearn 2001
roboticsoccersimulationteamandprovidesaninsightintothewayinwhichthesecomponentshavebeen
(incrementally)developed. Ourmaincontributionsincludeamulti-threadedthree-layeragentarchitecture,
a(cid:176)exibleagent-environmentsynchronizationscheme,accuratemethodsforobjectlocalizationandvelocity
estimationusingparticlefllters, alayeredskillshierarchy, ascoringpolicyforsimulatedsocceragentsand
an efiective team strategy. Ultimately, the thesis can be regarded as a handbook for the development of a
complete robotic soccer simulation team which also contains an introduction to robotic soccer in general
as well as a survey of prior research in soccer simulation. As such it provides a solid framework which
can serve as a basis for future research in the fleld of simulated robotic soccer. Throughout the project
UvA Trilearn 2001 has participated in two international robotic soccer competitions: the team reached
5th place at the German Open 2001 and 4th place at the o–cial RoboCup-2001 world championship.
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Acknowledgements
First of all the authors would like to thank each other for making their master’s graduation project a
successful and enjoyable experience. Our cooperation has always been very pleasant (even under stressful
circumstances or after an inevitable setback) and has enabled us to achieve the best of our abilities. The
research that is described in this thesis has truly been a team efiort and without either one of us the
resultwouldcertainlynothavebeenthesame. Furthermore,wethankourdirectsupervisorNikosVlassis
for his comments and suggestions regarding our research and for helping us with some of the di–cult
problems. Here we need to mention that Nikos also deserves credit for proofreading our thesis and for
helping us on the right track towards flnding a solution to the optimal scoring problem. Especially our
dicussion at the top of Seattle’s Space Needle proved to be very valuable in this respect. Special thanks
also go out to our professor Frans Groen for assigning us to the project and for guiding us through its
initial stages and to Elsevier Science for sponsoring our trip to Seattle. We would also like to thank the
followingpeoplefortheirfriendshipandsupportduringouryearsasmaster’sstudentsattheUniversityof
Amsterdam: Eugene Tuinstra, Eelco Schatborn, Tijs v.d. Storm, Mart de Graaf, Mans Scholten, Martin
Goede, Casper Kaandorp, Matthijs Spaan, Barry Koopen, Manuel de Vries and Claudius Blokker. Your
continuing presence during lectures and practical sessions and the many enjoyable hours that you have
given us away from the faculty have made our efiort of graduating worthwhile. Outside the university
we also owe thanks to our many close friends and relatives who have supported us throughout. Although
we cannot mention all of them, the flrst author (RdB) would especially like to thank his mother Elly
Tjoa for checking the spelling of parts of this thesis and most of all for her incredible support throughout
the entire efiort. Equally special thanks go out to his girlfriend Tessa Dirks who has gone through the
entire graduation experience with him and who has been very understanding and supportive at all times.
Without you two this thesis would surely never have happened! The second author (JK) would also like
to thank his parents Jan and Henny, girlfriend Barbara, little brother Sam, sister Laura and close friends
Rose, Meryam and Matthijs for their equal support and encouragement. Without a doubt all of you
deserve credit for our graduation.
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Contents
Abstract i
Acknowledgements iii
1 Introduction 1
1.1 The Robot World Cup Initiative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Robotic Soccer from a Multi-Agent Perspective . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Main Objectives and Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 Guide to the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 A Survey of Related Work 9
2.1 Prior Research within the Simulated Robotic Soccer Domain . . . . . . . . . . . . . . . . 9
2.1.1 CMUnited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.2 Essex Wizards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.3 FC Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.4 Cyberoos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.5 Karlsruhe Brainstormers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.6 Magma Freiburg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1.7 AT Humboldt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.1.8 Windmill Wanderers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.1.9 Mainz Rolling Brains. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.10 YowAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.11 Other Teams: Footux, RoboLog, Gemini . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Reference Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3 The RoboCup Soccer Server 17
3.1 Overview of the Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Sensor Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.1 Visual Sensor Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.2 Aural Sensor Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2.3 Body Sensor Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.3 Movement Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.4 Action Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.4.1 Kick Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.4.2 Dash and Stamina Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.4.3 Turn Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4.4 Say Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.4.5 Turn Neck Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
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3.4.6 Catch Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.4.7 Move Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.4.8 Change View Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.4.9 Actions Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5 Heterogeneous Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.6 Referee Model and Play Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.7 Coach Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.8 Summary of Main Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4 Agent Architecture 43
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.2 Functional Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.3 System Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.4 Flow of Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5 Synchronization 57
5.1 Introduction to the Problem of Synchronization . . . . . . . . . . . . . . . . . . . . . . . . 57
5.2 Timing of Incoming Messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.3 A Number of Synchronization Alternatives. . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.3.1 Method 1: External Basic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.3.2 Method 2: Internal Basic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.3.3 Method 3: Fixed External Windowing . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.3.4 Method 4: Flexible External Windowing . . . . . . . . . . . . . . . . . . . . . . . . 67
5.4 An Experimental Setup for Comparing the Alternatives . . . . . . . . . . . . . . . . . . . 69
5.5 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6 Agent World Model 75
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.2 Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.2.1 Environmental Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.2.2 Match Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.2.3 Object Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.2.4 Action Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.3 Retrieval Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.4 Update Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.4.1 Update from Body Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.4.2 Update from Visual Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.4.2.1 Agent Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
6.4.2.2 Agent Orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.4.2.3 Dynamic Object Information . . . . . . . . . . . . . . . . . . . . . . . . . 95
6.4.3 Update from Aural Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.5 Prediction Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.6 High-Level Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
7 Player Skills 109
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
7.2 Low-level Player Skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
7.2.1 Aligning the Neck with the Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
7.2.2 Turning the Body towards a Point . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
7.2.3 Turning the Back towards a Point . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
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