lecture 18 robots introduction.ppt
TRANSCRIPT
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Robots IntroductionBased on the lecture by Dr. Hadi MoradiUniversity of Southern California
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OutlineControl ApproachesFeedback ControlCyberneticsBraitenberg VehiclesArtificial IntelligenceEarly robotsRobotics TodayWhy is Robotics hard
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ControlSensing => ActionReactiveDont think, act: AnimalsDeliberativeThink hard, act later: ChessHybridThink and act in parallel: car racesBehavior-basedThink the way you act: human
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Reactive SystemsCollection of sense-act rulesStimulus-responseAdvantages:?Disadvantages?
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Reactive SystemsCollection of sense-act rulesStimulus-responseAdvantages:Inherently parallelNo/minimal stateVery fastNo memoryDisadvantagesNo planningNo learning
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Deliberative Systems3 phase model:SensePlanActExample: ChessAdvantages:?Disadvantages:?
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Deliberative Systems3 phase model:SensePlanActAdvantages:can planCan learnDisadvantages:Needs world modelSearching and planning are slowWorld model gets outdated
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Feedback ControlReact to the sensor changesFeedback control == self-regulationQ: What type of control system is it?
Feedback types:PositiveNegative
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- and + FeedbackNegative feedback:Regulates the state/outputExamples: Thermostat, bodies, Positive feedback:Amplifies the state/outputExamples: Stock marketThe first use: ancient Greek water systemRe-invented in the Renaissance for ovens
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W. Grey Walters Tortoise1953 Machina SpeculatrixSensors1 photocell, 1 bump sensor2 motorsReactive control
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W. Grey Walters TortoiseBehaviors: seeking light, head toward weak light, back away from bright light, turn and push (obstacle avoidance), recharge battery.Basis for creating adaptive behavior-based
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Turtle PrinciplesParsimony: simple is better e.g., clever recharging strategyExploration/speculation: keeps moving except when chargingAttraction (positive tropism): motivation to approach light Aversion (negative tropism): motivation to avoid obstacles, slopes Discernment: ability to distinguish and make choices productive or unproductive behavior, adaptationDucking
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Tortoise behaviorA path: a candle on top of the shell
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Tortoise behaviorTwo turtles: Like dancing
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New Tortoise
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QuestionHow does it do the charging?Note: When the battery is low, it goes for the light.
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Braitenberg VehiclesValentino Braitenberg early 1980sExtended Walters mode Based on analog circuits Direct connections between light sensors and motors Complex behaviors from very simple mechanisms
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Braitenberg VehiclesComplex behaviors from very simple mechanisms
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Braitenberg VehiclesBy varying the connections and their strengths, numerous behaviors result, e.g.: "fear/cowardice" - flees light "aggression" - charges into light "love" - following/hugging many others, up to memory and learning!Reactive control Later implemented on real robotsCheck: http://www.duke.edu/~mrz/braitenberg/braitenberg.htmlBots order Styrofoam cubes (16 min 30 sec)Tokyo Lecture 3 time 24:30-41:00
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Brief History1750: Swiss craftsman create automatons with clockwork to play tunes1917: Word Robot appeard in Karel Capeks play1938: Issac Asimov wrote a novel about robots1958: Unimation (Universal Automation) co started making die-casting robots for GM1960: Machine vision studies started1966: First painting robot installed in Byrne, Norway.1966: U.S.A.s robotic spacecraft lands on moon.1978: First PUMA (Programmable Universal Assembly) robot developed by Unimation.1979: Japan introduces the SCARA (Selective Compliance Assembly Robot Arm).
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Early Artificial Intelligence"Born" in 1955 at Dartmouth "Intelligent machine" would use internal models to search for solutions and then try them out (M. Minsky) => deliberative model! Planning became the tradition Explicit symbolic representations Hierarchical system organization Sequential execution
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Artificial IntelligenceEarly AI had a strong impact on early robotics Focused on knowledge, internal models, and reasoning/planning Eventually (1980s) robotics developed more appropriate approaches => behavior-based and hybrid control AI itself has also evolved... Early robots used deliberative controlIntelligence through construction (5 min 20 sec)Tokyo Lecture 2 time 27:40-33:00