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

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

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

• 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.


What’s a Robot?

• Mobile?• Autonomous• Softbots






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)


Motion for Robots

• Degrees of freedom


Different Sensor, Different Task

• SONAR– Obstacle avoidance

• Lasers– Range-finding

• Vision– Obstacle avoidance– Proprioception


Robot Architecture

• Designing a robot– Common features of many different robots

• Classical• Nouvelle AI (Situated automata)


Classical (aka SHAKEY)

• Theorem provers proved too general• No execution monitoring• Version 2

– Specialized programs (LLAs, ILAs)• Modeling uncertainty

– Learning with macro operators– PLANEX


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

http://hebb.cis.uoguelph.ca/~deb/Robotics/Notes/traditional/page5.html










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


Elephants Don’t Play Chess

• What does this mean?


(Physical) Symbol Systems

• Biologically implausible• Frame problem• Planning is hard

– NP-complete– Heuristics


Physical Grounding

• What’s the hypothesis?• Evolution

– What is Brooks’ argument?


Brooks’ Robots

• Allen• Tom & Jerry• Herbert• Genghis• Squirt

• Toto• Seymour• Gnats• Ant farm


Subsumption, what is good for?


Documents

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