Robots Introduction
Based on the lecture by Dr. Hadi MoradiUniversity of Southern California
Outline
• Control Approaches• Feedback Control• Cybernetics• Braitenberg Vehicles• Artificial Intelligence• Early robots• Robotics Today• Why is Robotics hard
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
Reactive Systems
• Collection of sense-act rules– Stimulus-response
• Advantages:– ?
• Disadvantages– ?
Reactive Systems
• Collection of sense-act rules– Stimulus-response
• Advantages:– Inherently parallel– No/minimal state– Very fast– No memory
• Disadvantages– No planning– No learning
Deliberative Systems
• 3 phase model:– Sense– Plan– Act
• Example: Chess• Advantages:
– ?• Disadvantages:
– ?
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• Disadvantages:– Needs world model– Searching and planning are slow– World model gets outdated
Feedback Control• React to the sensor changes• Feedback control == self-regulation• Q: What type of control system is it?
• Feedback types:– Positive– Negative
- 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
W. Grey Walter’s Tortoise
• 1953 • Machina Speculatrix• Sensors
– 1 photocell, – 1 bump sensor
• 2 motors• Reactive control
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
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
Tortoise behavior
• A path: a candle on top of the shell
Tortoise behavior
• Two turtles: Like dancing
New Tortoise
Question
• How does it do the charging?– Note: When the
battery is low, it goes for the light.
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
Braitenberg Vehicles
• Complex behaviors from very simple mechanisms
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• Bots order Styrofoam cubes (16 min 30 sec)
– Tokyo Lecture 3 time 24:30-41:00
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).
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
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
