1. Lecture 4-1CS251: Intro to AI/Lisp II Robots in Action

2. Lecture 4-1CS251: Intro to AI/Lisp II 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

3. Lecture 4-1CS251: Intro to AI/Lisp II 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.

4. Lecture 4-1CS251: Intro to AI/Lisp II What’s a Robot? Mobile? Autonomous Softbots

5. Lecture 4-1CS251: Intro to AI/Lisp II

6. Lecture 4-1CS251: Intro to AI/Lisp II

7. Lecture 4-1CS251: Intro to AI/Lisp II

8. Lecture 4-1CS251: Intro to AI/Lisp II

9. Lecture 4-1CS251: Intro to AI/Lisp II 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)

10. Lecture 4-1CS251: Intro to AI/Lisp II Motion for Robots Degrees of freedom

11. Lecture 4-1CS251: Intro to AI/Lisp II Different Sensor, Different Task SONAR –Obstacle avoidance Lasers –Range-finding Vision –Obstacle avoidance –Proprioception

12. Lecture 4-1CS251: Intro to AI/Lisp II Robot Architecture Designing a robot –Common features of many different robots Classical Nouvelle AI (Situated automata)

13. Lecture 4-1CS251: Intro to AI/Lisp II Classical (aka SHAKEY) Theorem provers proved too general No execution monitoring Version 2 –Specialized programs (LLAs, ILAs) Modeling uncertainty –Learning with macro operators –PLANEX

14. Lecture 4-1CS251: Intro to AI/Lisp II 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.htmlhttp://hebb.cis.uoguelph.ca/~deb/Robotics/Notes/traditional/page5.html

15. Lecture 4-1CS251: Intro to AI/Lisp II 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

16. Lecture 4-1CS251: Intro to AI/Lisp II Elephants Don’t Play Chess What does this mean?

17. Lecture 4-1CS251: Intro to AI/Lisp II (Physical) Symbol Systems Biologically implausible Frame problem Planning is hard –NP-complete –Heuristics

18. Lecture 4-1CS251: Intro to AI/Lisp II Physical Grounding What’s the hypothesis? Evolution –What is Brooks’ argument?

19. Lecture 4-1CS251: Intro to AI/Lisp II Brooks’ Robots Allen Tom & Jerry Herbert Genghis Squirt Toto Seymour Gnats Ant farm

20. Lecture 4-1CS251: Intro to AI/Lisp II Subsumption, what is good for?

21. Lecture 4-1CS251: Intro to AI/Lisp II