Bio Inspired Design - Lecture8. Bioprocessing – biobehaviours and group intelligence
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Transcript of Bio Inspired Design - Lecture8. Bioprocessing – biobehaviours and group intelligence
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Bio-Inspired Design 2011
Wb2436-05 (Entirely in English)
Prof. Dr. Tetsuo Tomiyama (3mE/BMechE/IMS)
Bio-Mechanical DesignMechanical Engineering
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©2011 Tetsuo Tomiyama
Lecture 8: March 2, 2011 (Wed)8:45-10:30, Room B
• Bioprocessing, Biosensing & Behavior• Society• Collaboration, Communication, Sensing• Group Behavior (Swarm Intelligence)• Simple Laws for Complex Behavior
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Animals Live in a Society
•Human•Individual•Family•Group•Community•Country
•Ant•Individual•Colony•Group•?
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What is a Society?
• Societal Structure <-> Behaviors• Physics
• Sensing, DNA, Etc.• Roles (Function)• Rules about Behaviors
• Rules• They Have a Society, So There Seem to Exist Rules• They Have Rules, So There Exist a Society
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Individual Behavior vs. GroupBehavior vs. Social Behavior
• Individuals Behave Following and Pursuing Its OwnInterests• Group Behavior as a Collection of Individual Behaviors• Social Behavior as a Collection of Group Behaviors• Coordination?
• Are Individuals Completely Free to Behave?• Requests, Instructions, Consultations, Negotiations?
• A Group or Society Have Their Own Interests• Collaboration• Coordination
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Individual Behavior as a Reflection ofSociety (or Group)
• The Society Dictates (or at Least Requests) GroupBehaviors
• The Group Dictates Individual Behaviors• Any “Anti-Social” Behaviors Resulted in
Disadvantages for Individuals• The Society Forms Benavioral Norms
• Women Choose Rich Men• (Intelligent) Women Choose Intelligent Men• Ladies Like Gentlemen
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Societal Behaviors
• Societal Behaviors• Collaboration
• Requires Information• Collecting Information = Sensing
• Requires Communication
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Collaboration
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Collaboration Requires Informationand Communication• How Do They Sense Outside Society?
• Bio-Sensing: Potential Field• Vision (Light)• Smell (Chemical)• Vibration• Voice (Ultrasonic)• Geomagnetism
• Humans Don’t Have Good Sensing Capabilities• Intelligence Compensate Poor Sensing Capabilities
• How Do They Communicate with Each Other?• Language
• Voice• Behavioral
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Limited Intelligence?
• How Are They Intelligent?• Individual Intelligence• Group Intelligence
• Fish• Zebra• Monkey• Ants• Bees
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Dogs
• Good Smelling Sense• Poor Vision?
• Static Objects 550m• Moving Objects 800m• Hound Dog 825m• Color Blind?
• Purple, Blue, Yellow
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Ants
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Ants: Very Social Insects
• Colony• Roles
• Queen• Female: Worker, Soldier, Forager• Female: Princess• Male
• Communication• Pheromone Based• Noise
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Ants
• Nose, Antenna• Pheromones• “Smell”
• Eyes• Sun (Orientation)• Vision
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Pigeon
• Homing Instinct• Geomagnetism
• Compass?• Sun
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Eels
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Salmons
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Language?
• Waggle Dance (Karl von Frisch)• Patterns• Direction• Distance (Waggling Time)• How Much
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Goose
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Sardines
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Society with a Leader• Monkeys, etc.• The Leader (Usually
Male)• Eats First, Most• Occupies Females
• FlatteringBehavior
• Finds Food, Water• Protect the Group
from Enemies
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Group without a Leader
• Fish• Maximum Results with Minimum Efforts
• “Group” Looks Like a Big Fish• Better Information about Food• Better Breeding Possibilities
• Simple Rules• Follow Other Fish• Sometimes Individual Decisions
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Can We Use This Knowledge?
• Group Behaviors of Biological Systems• Sensing• Communication• Information Processing
• Rules• Engineering Applications?
• Behaviors Simulated with Simple Rules
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Ant Colony Optimization• Ants Walk Around Randomly
• = No Pheromone is Sensed• If an Ant Finds Food, then Goes Back to the
Nest• Vision, Smell, Pheromone of Other Ants• Depositing Pheromone (1 or 2 Molecules) on the
Trail• If Found Pheromone Trail, Try to Get Food
• More Ants = More Pheromone• Learning Effect
• However, as Time Passes, PheromoneEvaporates• Shorter Paths Have More Chances of Collecting
More Pheromone• The Shortest Path can be Found, After Some Time
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群型テザード衛星(東工大) 親子型群ロボット(東工大)
クローラ型群ロボット(神戸大)
細胞型倉庫(東大)
蛇型群ロボット(東工大) 協調搬送ロボット(東北大)
群協調ロボット(東大) 群協調ロボット(理研)
自己組織化ロボット(機技研) 協調搬送ロボット(東北大)
Cellular Machines, SwarmIntelligence, Modular Machines
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Hirose Lab. Tokyo Institute of Technology
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http://www-robot.mes.titech.ac.jp/home_e.html
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Key: How Should Individuals ExhibitMeaningful Behaviors Collectively?
• How Should Individuals Obtain Global/Local Information?• Global Information
• Position, Orientation, Goal, Situation• Local Information
• Identity, Partner, Position, Potential Field• How Should Individuals Behave Globally?
• Emergence• Control• Coordination: Decision Making• Collaborative Behavior
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information
Communication
CellBasic Ideas
• Cellular Machines• Homogeneity• Distributed Information• Autonomy
• Flexibility• Fault Tolerance• Reconfigurability, Up/Down-Gradeability
• Local Communication = Local Information• No Central Control
• No Need to Design Global Structure• Introducing Self-Organization Capability
• Determining Strategic Configuration of a Production Facility duringOperations
• Various Conditions and Manufacturing Requirements
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Cellular Machines
•Cellular AutomaticWarehouse•Cellular Assembling System
•Assembling Cell(Manipulator) + VisionSystem•Production Information (PI)for Assembling
•Cellular Manufacturing System•Machining Cell (Manipulator)•Machining Information Added toPI
•Cellular RemanufacturingSystem
•Inspection Cell + Cleaning Cell•Self-Organization of CellularMachines
•How Can a Cellular SystemExhibit a “Structure”?•Design Support Tool ofManufacturing Systems
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Demonstration (Cellular ManufacturingSystem)
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Collaborative Behavior
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Movable Cellular Machines (LEGO Mindstorms)
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Self-Assembling Robot (AIST, JP)
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Self-Assembling Robot
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Self-Assembling Robot
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Global Information vs. LocalInformation
• Local Sensing• Local Information
• Can We Build Global Information from LocalInformation Only?• Position• Deadlock
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Minimum Intelligence
• Minimum “Intelligence” toPerform a Task• Delivery of Goods from A
to B with High Efficiency• No Collisions, No Non-
Productive Moves• Can We Implement Very
Simple Rules to Do So?
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How Should They Be Intelligent to BeEfficient and Productive?
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Conclusions
• Swarm Robotics• Interesting Ideas
• Local Information, Local Decision Making• Collaborations• Global Behavior/Function Emergence
• Can Simple “Rules” Help?• Or Big Intelligence?
• Applications• Space, Extremely Dangerous Situations• Relatively Lower Cost