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Robots Introduction

Robots Introduction. Based on the lecture by Dr. Hadi Moradi University of Southern California. Outline. Control Approaches Feedback Control Cybernetics Braitenberg Vehicles Artificial Intelligence Early robots Robotics Today Why is Robotics hard. Control. Sensing => Action

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Robots Introduction

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  1. Robots Introduction Based on the lecture by Dr. Hadi Moradi University of Southern California

  2. Outline • Control Approaches • Feedback Control • Cybernetics • Braitenberg Vehicles • Artificial Intelligence • Early robots • Robotics Today • Why is Robotics hard

  3. Control • Sensing => Action • Reactive • Don’t think, act: Animals • Deliberative • Think hard, act later: Chess • Hybrid • Think and act in parallel: car races • Behavior-based • Think the way you act: human

  4. Reactive Systems • Collection of sense-act rules • Stimulus-response • Advantages: • ? • Disadvantages • ?

  5. Reactive Systems • Collection of sense-act rules • Stimulus-response • Advantages: • Inherently parallel • No/minimal state • Very fast • No memory • Disadvantages • No planning • No learning

  6. Deliberative Systems • 3 phase model: • Sense • Plan • Act • Example: Chess • Advantages: • ? • Disadvantages: • ?

  7. Deliberative Systems • 3 phase model: • Sense • Plan • Act • Advantages: • can plan • Can learn • Disadvantages: • Needs world model • Searching and planning are slow • World model gets outdated

  8. Feedback Control • React to the sensor changes • Feedback control == self-regulation • Q: What type of control system is it? • Feedback types: • Positive • Negative

  9. - and + Feedback • Negative feedback: • Regulates the state/output • Examples: Thermostat, bodies, … • Positive feedback: • Amplifies the state/output • Examples: Stock market • The first use: ancient Greek water system • Re-invented in the Renaissance for ovens

  10. W. Grey Walter’s Tortoise • 1953 • Machina Speculatrix • Sensors • 1 photocell, • 1 bump sensor • 2 motors • Reactive control

  11. W. Grey Walter’s Tortoise • Behaviors: • seeking light, • head toward weak light, • back away from bright light, • turn and push (obstacle avoidance), • recharge battery. • Basis for creating adaptive behavior-based

  12. Turtle Principles • Parsimony: simple is better • e.g., clever recharging strategy • Exploration/speculation: keeps moving • except when charging • Attraction (positive tropism): • motivation to approach light • Aversion (negative tropism): • motivation to avoid obstacles, slopes • Discernment: ability to distinguish and make choices • productive or unproductive behavior, adaptation Ducking

  13. Tortoise behavior • A path: a candle on top of the shell

  14. Tortoise behavior • Two turtles: Like dancing

  15. New Tortoise

  16. Question • How does it do the charging? • Note: When the battery is low, it goes for the light.

  17. Braitenberg Vehicles • Valentino Braitenberg • early 1980s • Extended Walter’s mode • Based on analog circuits • Direct connections between light sensors and motors • Complex behaviors from very simple mechanisms

  18. Braitenberg Vehicles • Complex behaviors from very simple mechanisms

  19. Braitenberg Vehicles • By varying the connections and their strengths, numerous behaviors result, e.g.: • "fear/cowardice" - flees light • "aggression" - charges into light • "love" - following/hugging • many others, up to memory and learning! • Reactive control • Later implemented on real robots • Check: http://www.duke.edu/~mrz/braitenberg/braitenberg.html • Botsorder Styrofoam cubes(16 min 30 sec) • Tokyo Lecture 3 time 24:30-41:00

  20. Brief History • 1750: Swiss craftsman create automatons with clockwork to play tunes • 1917: Word Robot appeard in Karel Capek’s play • 1938: Issac Asimov wrote a novel about robots • 1958: Unimation (Universal Automation) co started making die-casting robots for GM • 1960: Machine vision studies started • 1966: First painting robot installed in Byrne, Norway. • 1966: U.S.A.’s robotic spacecraft lands on moon. • 1978: First PUMA (Programmable Universal Assembly) robot developed by Unimation. • 1979: Japan introduces the SCARA (Selective Compliance Assembly Robot Arm).

  21. Early Artificial Intelligence • "Born" in 1955 at Dartmouth • "Intelligent machine" would use internal models to search for solutions and then try them out (M. Minsky) => deliberative model! • Planning became the tradition • Explicit symbolic representations • Hierarchical system organization • Sequential execution

  22. Artificial Intelligence • Early AI had a strong impact on early robotics • Focused on knowledge, internal models, and reasoning/planning • Eventually (1980s) robotics developed more appropriate approaches => behavior-based and hybrid control • AI itself has also evolved... • Early robots used deliberative control • Intelligence through construction (5 min 20 sec) • Tokyo Lecture 2 time 27:40-33:00

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