Download Introduction to Multi

Introduction to Robotics
& Multi-robot systems
Speaker : Wen-Chieh Fang
Time : 2005/08
Agenda
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The Study of Agency
Related Courses
Mobile robots
Architecture
 Hierarchical Paradigm
 Reactive Paradigm
 Hybrid Paradigm
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Communication
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5 Categories of Communication
Communication Structure
What Do Robots Say to Each Other?
Languages for multi-agents
Applications
 Multi-robot Sensing
 Sensory coverage
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
Control
Reference
The Study of Agency
(after Stone and Veloso 2002)
[Murphy 2000 slides]
Distributed
Artificial
Intelligence
Distributed
Problem
Solving
Single computer:
•How to decompose task?
•How to synthesize solutions?
How to solve problems
Or meet goals by
“divide and conquer”
MultiAgent
Systems
Divide among agents:
•Who to subcontract to?
•How do they cooperate?
Related Courses
 Robotics
 Artificial Intelligence
 Distributed Artificial Intelligence (DAI)
 Multi-agent systems
 Animal behavior (optional)
Mobile robots
 Navigation
 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.)
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Motion Control problem
World Modeling problem
Localization problem
Planning problem
Architecture problem
Architecture
 Hierarchical Paradigm
 Reactive Paradigm
 Hybrid Paradigm
Hierarchical Paradigm
 Organization
World model:
1. A priori rep
2. Sensed info
3. Cognitive
SENSE
PLAN
ACT
Reactive Paradigm
 Vertical decomposition of tasks
Hybrid Paradigm
 Organization
PLAN
SENSE
ACT
5 Categories of Communication
[Murphy 2000 slides]
 Infinite
 comms are free
 Motion
 costs as much to communicate as it would to move
 ex. Box pushing (if other robot can feel the box, it’s comms)
 Low
 comms costs more than moving from one location to
another
 Zero
 no communication between agents
 Topology
 Broadcast, address, tree, graph
Communication Structure
 Interaction via Environment :
 Environment is the
communication medium (a
shared memory)
 Interaction via Sensing :
 Without explicit communication
Adopted from [ Parker et.al.2003 ]
 Interaction via Communications :
 Explicit communication by either
directed or broadcast intentional
messages
Adopted from [ Yoshida et.al. 1994 ]
What Do Robots Say to
Each Other? [Murphy 2000 slides]
 How do they “talk”?
 Implicit: signaling, postures, smell
 Explicit: language
 Who does the talking?
 “the boss” -Centralized control
 Everybody - Distributed control
What do Robots Say?
(after Jung and Zelinsky 02)
[Murphy 2000 slides]
 Communication without meaning preservation
 Emitter can’t interpret its own signal
 Receiver reacts in a specific way (stimulus-response)
 Ex. Mating displays, bacteria emit chemicals
 Communication with meaning preservation
 Shared common representation
 Ex. Ant leaves pheromone trail to food, itself & peers can
follow
 Ex. Wolves leave scent markings
Languages for multi-agents
 To abstract the important information and minimize
explicit communication
 Does an increase on the amount of transmitted data
imply better performance? [ Castelpietra et. al. 2000 ]
 How to make agents to speak the “ same language”?
(how to translate syntactically and semantically the
data or information structures of the sender to the
receiver?) [ Ye et. al. 2002 ]
 How to make agents mean the same “meaning” when
they communicate? (how to make sure that agents use
the same ontology?) [ Ye et. al. 2002 ]
Multi-robot Sensing
[Murphy 2000]
 Proprioceptive sensors
(which robots measures a
signal originating within itself):
 Shaft encoder
 GPS
 Proximity sensors :
 Sonar or ultrasonics
 Infrared (IR)
 Bump and feeler sensors
 Computer Vision
 Range from vision
 Stereo camera pairs
 Light stripers
 Laser ranging
Adopted from [ Werger & Mataric 2000 ]
Sensory coverage
 Topics
 Target tracking/search
 Variations
 Numbers & speeds of
sensor & targets
 Communication, sensing
& movement capabilities
 Terrain
 Predictability of targets
 Multi-sensor fusion
Adopted from [ Jung & Sukhatme 2002 ]
Control
 Centralized control
 Distributed control
Reference
 English reference
 R. R. Murphy, Introduction to AI Robotics. The MIT Press, 2000.
 Chinese reference
 彼得‧曼瑟, 費斯‧德魯修著, “機器人的進化:人工智慧與機器人學
的新世紀”, 商周出版, 2002
 羅德尼‧布魯克斯著, "我們都是機器人：人機合一的大時代", 究
竟, 2003
 漢斯‧摩拉維克著, "機器人：由機器邁向超越人類心智之路", 台
灣商務, 2004
Reference
 [ 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.