Introduction to Introduction to Robotics & Multi-robot Robotics & Multi-robot systemssystemsSpeaker : Wen-Chieh FangSpeaker : Wen-Chieh Fang

Time : 2005/08Time : 2005/08

AgendaAgenda

The Study of Agency The Study of Agency Related CoursesRelated Courses Mobile robotsMobile robots ArchitectureArchitecture

Hierarchical ParadigmHierarchical Paradigm Reactive ParadigmReactive Paradigm Hybrid ParadigmHybrid Paradigm

CommunicationCommunication 5 Categories of Communication 5 Categories of Communication Communication StructureCommunication Structure What Do Robots Say to Each Other?What Do Robots Say to Each Other? Languages for multi-agentsLanguages for multi-agents

ApplicationsApplications Multi-robot SensingMulti-robot Sensing Sensory coverageSensory coverage

ControlControl ReferenceReference

The Study of AgencyThe Study of Agency(after Stone and Veloso 2002)(after Stone and Veloso 2002) [Murphy 2000 slides][Murphy 2000 slides]

DistributedArtificial

Intelligence

DistributedProblemSolving

Multi-Agent

Systems

How to solve problemsOr meet goals by

“divide and conquer”

Single computer:•How to decompose task?•How to synthesize solutions?

Divide among agents:•Who to subcontract to?•How do they cooperate?

Related CoursesRelated Courses

RoboticsRobotics Artificial IntelligenceArtificial Intelligence

Distributed Artificial Intelligence (DAI)Distributed Artificial Intelligence (DAI)

Multi-agent systemsMulti-agent systems Animal behavior (optional)Animal behavior (optional)

Mobile robotsMobile robots

NavigationNavigation Maximum Navigation Test (MNT)Maximum Navigation Test (MNT)

The robot is placed in an environment that is unknown, large, complex and dynamic. After a time needed by the robot to explore the environment, the robot must be able to go to any selected place, trying to minimize a cost function (e.g. time, energy, etc).

Mobile robots (Cont.)Mobile robots (Cont.)

Motion Control problemMotion Control problem World Modeling problemWorld Modeling problem Localization problemLocalization problem Planning problemPlanning problem Architecture problem Architecture problem

ArchitectureArchitecture

Hierarchical ParadigmHierarchical Paradigm Reactive ParadigmReactive Paradigm Hybrid ParadigmHybrid Paradigm

Hierarchical ParadigmHierarchical Paradigm

OrganizationOrganizationPLANSENSE ACT

World model:1. A priori rep2. Sensed info3. Cognitive

Reactive ParadigmReactive Paradigm

Vertical decomposition of tasksVertical decomposition of tasks

Hybrid ParadigmHybrid Paradigm

OrganizationOrganization

SENSE

PLAN

ACT

5 Categories of Communication 5 Categories of Communication [Murphy 2000 slides][Murphy 2000 slides]

InfiniteInfinite comms are freecomms are free

Motion Motion costs as much to communicate as it would to move costs as much to communicate as it would to move

ex. Box pushing (if other robot can feel the box, it’s comms)ex. Box pushing (if other robot can feel the box, it’s comms)

Low Low comms costs more than moving from one location to anothercomms costs more than moving from one location to another

ZeroZero no communication between agentsno communication between agents

TopologyTopology Broadcast, address, tree, graphBroadcast, address, tree, graph

Communication StructureCommunication Structure

Interaction via Environment :Interaction via Environment : Environment is the Environment is the

communication medium (a communication medium (a shared memory) shared memory)

Interaction via Sensing :Interaction via Sensing : Without explicit communicationWithout explicit communication

Interaction via Communications :Interaction via Communications : Explicit communication by either Explicit communication by either

directed or broadcast intentional directed or broadcast intentional messagesmessages

Adopted from [ Parker et.al.2003

]

Adopted from [ Yoshida et.al. 1994

]

What Do Robots Say to What Do Robots Say to Each Other? Each Other? [Murphy 2000 slides][Murphy 2000 slides]

How do they “talk”?How do they “talk”? Implicit: signaling, postures, smellImplicit: signaling, postures, smell Explicit: languageExplicit: language

Who does the talking?Who does the talking? ““the boss” -Centralized controlthe boss” -Centralized control Everybody - Distributed controlEverybody - Distributed control

What do Robots Say? What do Robots Say? (after Jung and Zelinsky 02) (after Jung and Zelinsky 02) [Murphy 2000 slides][Murphy 2000 slides]

Communication without meaning preservationCommunication without meaning preservation Emitter can’t interpret its own signal Emitter can’t interpret its own signal Receiver reacts in a specific way (stimulus-response)Receiver reacts in a specific way (stimulus-response) Ex. Mating displays, bacteria emit chemicalsEx. Mating displays, bacteria emit chemicals

Communication with meaning preservationCommunication with meaning preservation Shared common representationShared common representation Ex. Ant leaves pheromone trail to food, itself & peers can folloEx. Ant leaves pheromone trail to food, itself & peers can follo

ww Ex. Wolves leave scent markingsEx. Wolves leave scent markings

Languages for multi-agentsLanguages for multi-agents

To abstract the important information and minimize expTo abstract the important information and minimize explicit communicationlicit communication

Does an increase on the amount of transmitted data imDoes an increase on the amount of transmitted data imply better performance?ply better performance? [ Castelpietra et. al. 2000 ]

How to make agents to speak the “ same language”? How to make agents to speak the “ same language”? (how to translate (how to translate syntacticallysyntactically and and semanticallysemantically the dat the data or information structures of the sender to the receivea or information structures of the sender to the receiver?)r?) [ Ye et. al. 2002 ]

How to make agents mean the same “meaning” when tHow to make agents mean the same “meaning” when they communicate? (how to make sure that agents use hey communicate? (how to make sure that agents use the same the same ontologyontology?)?) [ Ye et. al. 2002 ]

Multi-robot Sensing Multi-robot Sensing [Murphy [Murphy

2000]2000]

Proprioceptive sensors (Proprioceptive sensors (wwhich robots measures a signal hich robots measures a signal originating within itselforiginating within itself):): Shaft encoderShaft encoder GPSGPS

Proximity sensors :Proximity sensors : Sonar or ultrasonicsSonar or ultrasonics Infrared (IR)Infrared (IR) Bump and feeler sensorsBump and feeler sensors

Computer VisionComputer Vision Range from visionRange from vision

Stereo camera pairsStereo camera pairs Light stripersLight stripers Laser rangingLaser ranging

Adopted from [ Werger & Mataric 2000 ]

Sensory coverageSensory coverage

TopicsTopics Target tracking/searchTarget tracking/search VariationsVariations

Numbers & speeds of Numbers & speeds of sensor & targetssensor & targets

Communication, sensing Communication, sensing & movement capabilities& movement capabilities

TerrainTerrain Predictability of targetsPredictability of targets Multi-sensor fusionMulti-sensor fusion

Adopted from [ Jung & Sukhatme 2002 ]

ControlControl

Centralized controlCentralized control Distributed controlDistributed control

ReferenceReference

English referenceEnglish reference R. R. Murphy, Introduction to AI Robotics. The MIT Press, 2000.R. R. Murphy, Introduction to AI Robotics. The MIT Press, 2000.

Chinese referenceChinese reference 彼得‧曼瑟彼得‧曼瑟 , , 費斯‧德魯修著費斯‧德魯修著 , “, “機器人的進化機器人的進化 ::人工智慧與機器人工智慧與機器人學的新世紀”人學的新世紀” ,, 商周出版商周出版 , 2002, 2002

羅德尼‧布魯克斯著羅德尼‧布魯克斯著 , ", "我們都是機器人：人機合一的大時代我們都是機器人：人機合一的大時代 ", ", 究竟究竟 , 2003, 2003

漢斯‧摩拉維克著漢斯‧摩拉維克著 , ", "機器人：由機器邁向超越人類心智之路機器人：由機器邁向超越人類心智之路 ", ",

台灣商務台灣商務 , 2004, 2004

ReferenceReference

[ Castelpietra et. al. 2000 ] C. Castelpietra, L. Iocchi, D. Nardi, and R. Rosati, “Coordination in multi-agent autonomous cognitive robotic systems,” in Proceedings of 2nd International Cognitive Robotics Workshop, 2000. [ Ye et. al. 2002 ] Y. Ye, S. Boies, J. Liu, and X. Yi, “Collective perception in massive, open, and heterogeneous multi-agent environment,” in Proceedings of 1st International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS’02), 2002.