Multiagent Robotic Systems

310 Pages·2001·9.502 MB·English

by  Jiming Liu, Jianbing Wu

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MULTI -AGENT
ROBOTIC
SYSTEMS
Jiming Liu
Jianbing Wu
CRC Press
Boca Raton London New York Washington, D.C.
©2001 CRC Press LLC
disclaimer Page 1 Tuesday, April 10, 2001 4:41 PM
Royalties from this book will be donated
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Library of Congress Cataloging-in-Publication Data
Liu, Jiming, 1962-
Multi-Agent robotic systems / Jiming Liu, Jianbing Wu.
p. cm.—(International series on computational intelligence)
Includes bibliographical references and index.
ISBN 0-8493-2288-X (alk. paper)
1. Robots—Control systems. 2. Intelligent agents (Computer software) I. Wu,
Jianbing. II. Title. III. CRC Press international series on computational intelligence
TJ211.35 .L58 2001 2001025397

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Preface
Not everything thatcan be counted counts, andnot everything that
countscanbecounted.1
An autonomous agent is a computational system that acquires and analyzes
sensory dataorexternal stimulusandexecutes behaviorsthatproduceeffects in
the environment. It decides for itself how to relate sensory data to its behav-
iors in its efforts to attain certain goals. Such a system is able to deal with un-
predictableproblems,dynamicallychangingsituations,poorlymodeledenviron-
ments,orconflictingconstraints.
The motivation behind the research and development in multi-agent robotic
systems comes from the fact that the decentralized multi-robotapproach has a
numberofadvantagesovertraditionalsinglecomplexroboticsystemsapproaches.
Distributedrobotscan readilyexhibitthe characteristics of structuralflexibility,
1AsignhanginginAlbertEinstein’sofficeatPrinceton.
©2001 CRC Press LLC
reliability through redundancy, simple hardware, adaptability, reconfigurability,
and maintainability.Therobotscan interactwiththeirlocalenvironmentsinthe
courseofcollectiveproblem-solving.Respondingtodifferentlocalconstraintsre-
ceivedfromtheirtaskenvironments,theymayselectandexhibitdifferentbehav-
iorpatterns, such as avoidance, following,aggregation, dispersion,homing,and
wandering.Thesebehaviorsarepreciselycontrolledthroughanarrayofparame-
ters(suchasmotiondirection,timing,lifespan,age,etc.),whichmaybecarefully
predefinedordynamicallyacquiredbytherobotsbasedoncertaincomputational
mechanisms.
Inordertosuccessfullydevelopmulti-agentroboticsystems, thekeymethod-
ologicalissuesmustbecarefullyexamined.Atthesametime,theunderlyingcom-
putational models and techniques for multi-agent systems engineering must be
thoroughlyunderstood.AsacompaniontoAutonomousAgentsandMulti-Agent
Systems by Jiming Liu, World Scientific Publishing, 2001, this book is about
learning, adaptation, and self-organization in decentralized autonomous robots.
Theaimsofthebookaretoprovideaguidedtourofthepioneeringworkandthe
majortechnicalissuesinmulti-agentroboticsresearch(PartI),andtogiveanin-
depthdiscussiononthecomputationalmechanismsforbehaviorengineeringina
groupofautonomousrobots(PartsIItoIV).Throughasystematicexamination,
weaim tounderstandtheinterrelationshipsbetweentheautonomyofindividual
robotsand theemerged globalbehaviorpropertiesof thegroupinperforminga
cooperative task. Toward this end, we describe the essential buildingblocks in
thearchitectureofautonomousmobilerobotswithrespecttotherequirementson
localbehaviorconditioningandgroupbehaviorevolution.
This book has a number of specially designed features to enable readers to
understandthetopicspresentedandtoapplythetechniquesdemonstrated.These
featuresare:
1. Thecontentshaveabalancedemphasisontherecentandpioneeringwork,
thetheoretical/computationalaspects,andtheexperimental/practicalissues
ofmulti-agentroboticsystems.
2. The materials are structured in a systematic, coherent manner with
implementationdetails,comprehensiveexamples,andcasestudies.
3. Many graphical illustrations are inserted to explain and highlight the
importantnotionsandprinciples.
4. MATLAB toolboxes for multi-agent robotics research, experimentation,
and learning are provided, which are available for free download
from
http:==www:.crcpress:com=us=ElectronicProducts=
downandup:asp?mscssid=
©2001 CRC Press LLC
After reading this book, we hope that readers will be able to appreciate the
strengthsandusefulnessofvariousapproachesinthedevelopmentandapplication
of multi-agentroboticsystems. They willbe able to thoroughlyunderstand the
followingfiveissues:
1. Why and how do we develop and experimentally test the computational
mechanisms forlearningandevolvingsensory-motorcontrolbehaviorsin
autonomousrobots.
2. Howdoweenablegrouprobotstoconvergetoafinitenumberofdesirable
taskstatesthroughgrouplearning.
3. Whataretheeffectsofthelocallearningmechanismsontheemergenceof
globalbehaviors.
4. How do we design and develop evolutionary algorithm-based behavior
learningmechanismsfortheoptimalemergenceof(group)behaviors.
5. How do we use decentralized, self-organizing autonomous robots to
performcooperativetasksinanunknownenvironment.
JimingLiu
JianbingWu
Summer2001
©2001 CRC Press LLC
Acknowledgements
First,wewouldliketothankthepioneersandfellowresearchersaswellastheau-
thorsofbooks,papers,andarticlesinthefieldsofintelligentsystems,autonomous
agentsandmulti-agentsystems,androboticsforprovidinguswithinsights,ideas,
andmaterialsinpreparingthesurveysinthisbook.
Second,wewishtoofferourthankstoourhomeinstitutions,HongKongBap-
tistUniversity(HKBU)andUniversityofCalgary,forprovidinguswithpleasant
workingenvironments that enable us to pursue our research. Without these en-
vironments, it could take longer for us to come up with this synthesis. Part of
thisbookwas writtenduringJiming’ssabbatical leave intheComputerScience
Department ofStanfordUniversity.HerewewouldliketothankProf.Oussama
KhatibforhiskindinvitationandalsothankHKBUforgrantingthisopportunity.
Third,wewishtoacknowledgetheresearch grantssupportprovidedbyHong
KongBaptistUniversityundertheschemeofFacultyResearchGrantsandbythe
Hong KongResearch Grants Councilunder the scheme of Earmarked Research
Grants.Withoutthatsupport,thetheoreticalandexperimentalstudiesreportedin
thisbookwouldnotbepossible.
Inaddition,wewishtothankX.Lai,K.P.Chow,andK.K.Huiforproviding
research assistance in some of the related studies. Our special thanks go to the
editoroftheseries,Prof.LakhmiC.Jain,forhisvisionandencouragement,and
to Jerry Papke and Dawn Mesa of CRC Press for professionally managing and
handlingthisbookproject.WealsowanttothankMadelineLeighofCRCPress
forcarefullyeditingthedraftversionofthisbook.
Andfinally,toourfamilies,toMeilee,Isabella,andBernicefromJimingLiu,
andtoAudreyfromJianbingWu,ourheartfeltthanksfortheirlove,inspiration,
support,andencouragement.
©2001 CRC Press LLC
OtherCredits
Grateful acknowledgement is made to IEEE and ACM for permission to reuse
someofourIEEE/ACM-copyrightedmaterialinthisbook.
PortionsofJimingLiuetal.,Learningcoordinatedmaneuversincomplexenvi-
ronments:aSUMOexperiment,ProceedingsoftheIEEE/IEECongressonEvo-
lutionaryComputation(CEC’99),pages 343-349,Washington,D.C., July1999,
arereusedinChapter10.PortionsofJimingLiuandJianbingWu,Evolutionary
group robots for collective world modeling, Proceedings of the Third Interna-
tionalConference on AutonomousAgents (AGENTS’99),1999,ACM Press, are
reusedinChapters12and13.
Figures 6.2, 6.11, 9.1-9.3, and 9.5-9.13 and Tables 7.1 and 9.1 are adopted, and
Figures 6.15, 7.3(a), 8.6(a), 8.7(a), 8.8(a), 8.9(a), and 8.14(b) are modified, based
on thefigures and tablesinJimingLiu, JianbingWu, and Y. Y. Tang, Onemer-
gence of group behavior in a genetically controlled autonomous agent system,
ProceedingsoftheIEEEInternationalConferenceonEvolutionaryComputation
(ICEC’98),pages470-475,Anchorage,May1998.
Figures 11.1 and 11.4-11.10 are adopted, and Figures 11.2 and 11.3 are modi-
fied,basedonthefiguresinJimingLiu,JianbingWu,andXunLai,Analyticaland
experimental results on multiagentcooperativebehavior evolution,Proceedings
of the the IEEE/IEE Congress on Evolutionary Computation (CEC’99), pages
1732-1739,Washington,D.C.,July1999.
Figures 12.3, 12.4, 12.12, 13.5-13.13, and 14.28 are adopted, and Figures 13.3
and 13.4 and Table 13.1 are modified, based on the figures and table in Jiming
Liu, JianbingWu, andDavid A. Maluf,Evolutionaryself-organizationofan ar-
tificial potential field map with a group of autonomous robots, Proceedings of
theIEEE/IEECongressonEvolutionaryComputation(CEC’99),pages350-357,
Washington,D.C.,July1999.
Omissionsofcreditacknowledgementinthisbook,ifany,willbecorrectedin
futureeditions.
JimingLiu
JianbingWu
Summer2001
©2001 CRC Press LLC
Contents
I Motivation, Approaches, and Outstanding Issues
1 Why Multiple Robots?
1.1 Advantages
1.2 MajorThemes
1.3 Agents and Multi-Agent Systems
1.4 Multi-Agent Robotics
2 Toward Cooperative Control
2.1 Cooperation-Related Research
2.1.1 Distributed Artificial Intelligence
2.1.2 DistributedSystems
2.1.3 Biology
2.2 Learning,Evolution,andAdaptation
2.3 Design of Multi-Robot Control
3 Approaches
3.1 Behavior-BasedRobotics
3.2 CollectiveRobotics
3.3 EvolutionaryRobotics
3.4 InspirationfromBiologyandSociology
3.5 Summary
©2001 CRC Press LLC