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Understanding Robotics and AI in CS251: A Comprehensive Overview

This announcement outlines key aspects of the CS251 course on Artificial Intelligence and Lisp, focusing on robotics. Key topics include an introduction to Asimov's Three Laws of Robotics, the structure of the course project, late policy, and homework assignments. Students will learn about robotics fundamentals, sensor and actuator technology, robot architecture, and various approaches including classical robotics. Key concepts like motion, situational awareness, and planning amidst uncertainty will be explored. Stay updated on project guidelines and expectations!

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Understanding Robotics and AI in CS251: A Comprehensive Overview

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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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