Robots in Action

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

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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. - PowerPoint PPT Presentation

Transcript of Robots in Action

Page 1: Robots in Action

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

Robots in Action

Page 2: Robots in Action

Lecture 4-1 CS251: 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

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Lecture 4-1 CS251: 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.

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What’s a Robot?

• Mobile?

• Autonomous

• Softbots

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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)

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Motion for Robots

• Degrees of freedom

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Different Sensor, Different Task

• SONAR– Obstacle avoidance

• Lasers– Range-finding

• Vision– Obstacle avoidance– Proprioception

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Robot Architecture

• Designing a robot– Common features of many different robots

• Classical

• Nouvelle AI (Situated automata)

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Classical (aka SHAKEY)

• Theorem provers proved too general

• No execution monitoring

• Version 2– Specialized programs (LLAs, ILAs)

• Modeling uncertainty

– Learning with macro operators– PLANEX

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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

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Elephants Don’t Play Chess

• What does this mean?

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(Physical) Symbol Systems

• Biologically implausible

• Frame problem

• Planning is hard– NP-complete– Heuristics

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Physical Grounding

• What’s the hypothesis?

• Evolution– What is Brooks’ argument?

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Brooks’ Robots

• Allen

• Tom & Jerry

• Herbert

• Genghis

• Squirt

• Toto

• Seymour

• Gnats

• Ant farm

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Subsumption, what is good for?

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