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Robots in Action

Robots in Action. Announcements. Feedback response Late policy (Some credit, helps grading) Structure of course project (Tyranny of the majority, grading) PowerPoint vs. chalk talk: doing the reading Homework assigned today Course project descriptions. Asimov’s Three Laws.

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Robots in Action

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  1. Robots in Action CS251: Intro to AI/Lisp II

  2. Announcements • Feedback response • Late policy (Some credit, helps grading) • Structure of course project (Tyranny of the majority, grading) • PowerPoint vs. chalk talk: doing the reading • Homework assigned today • Course project descriptions CS251: Intro to AI/Lisp II

  3. Asimov’s Three Laws • A robot may not injure a human being, or, through inaction, allow a human being to come to harm. • A robot must obey the orders given it by human beings except where such orders would conflict with the First Law. • A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. CS251: Intro to AI/Lisp II

  4. What’s a Robot? • Mobile? • Autonomous • Softbots CS251: Intro to AI/Lisp II

  5. CS251: Intro to AI/Lisp II

  6. CS251: Intro to AI/Lisp II

  7. CS251: Intro to AI/Lisp II

  8. CS251: Intro to AI/Lisp II

  9. Snips and Snails and Puppy Dog Tails, that’s what robots are made of • Effectors • Actuators • Degrees of freedom • Sensors • Proprioception (Looking at your own hand) CS251: Intro to AI/Lisp II

  10. Motion for Robots • Degrees of freedom CS251: Intro to AI/Lisp II

  11. Different Sensor, Different Task • SONAR • Obstacle avoidance • Lasers • Range-finding • Vision • Obstacle avoidance • Proprioception CS251: Intro to AI/Lisp II

  12. Robot Architecture • Designing a robot • Common features of many different robots • Classical • Nouvelle AI (Situated automata) CS251: Intro to AI/Lisp II

  13. Classical (aka SHAKEY) • Theorem provers proved too general • No execution monitoring • Version 2 • Specialized programs (LLAs, ILAs) • Modeling uncertainty • Learning with macro operators • PLANEX CS251: Intro to AI/Lisp II

  14. SHAKEY • Conclusions • Limited ability to handle unexpected outcomes • Each move took 1 hour of computing time • High probability of failure • STRIPS produced good plans • Sensory interpretation primitive From http://hebb.cis.uoguelph.ca/~deb/Robotics/Notes/traditional/page5.html CS251: Intro to AI/Lisp II

  15. Situated Automata • Is classical robotics too difficult? • Toss out the representation • Embedded agents • Model the world as interacting automata • Physical environment + Agent • Local state of one = f(Signals from other) • Flakey CS251: Intro to AI/Lisp II

  16. Elephants Don’t Play Chess • What does this mean? CS251: Intro to AI/Lisp II

  17. (Physical) Symbol Systems • Biologically implausible • Frame problem • Planning is hard • NP-complete • Heuristics CS251: Intro to AI/Lisp II

  18. Physical Grounding • What’s the hypothesis? • Evolution • What is Brooks’ argument? CS251: Intro to AI/Lisp II

  19. Allen Tom & Jerry Herbert Genghis Squirt Toto Seymour Gnats Ant farm Brooks’ Robots CS251: Intro to AI/Lisp II

  20. Subsumption, what is good for? CS251: Intro to AI/Lisp II

  21. CS251: Intro to AI/Lisp II

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