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Behavior Control for Robotic Exploration of Planetary Surfaces - PowerPoint PPT Presentation


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Written by Erann Gat, Rajiv Desai, Robert Ivlev, John Loch and David P Miller Presented By Tony Morelli 9/30/2004. Behavior Control for Robotic Exploration of Planetary Surfaces. Abstract. Describes robots developed at JPL (Jet Propulsion Laboratory)

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Presentation Transcript
abstract
Abstract
  • Describes robots developed at JPL (Jet Propulsion Laboratory)
  • Demonstrate using behavior-control approach to control small robots on planetary surfaces
  • Behavior-Control uses very little computation.
introduction
Introduction
  • Cannot remote control robots from Earth because of the delay
  • Size is limited by power, not physical size
  • 3 ways to power a robot
    • Radioisotope Thermal Generators (decay of Plutonium)
    • Photovoltaic cells – Require heavy batteries
    • Non-Rechargable batteries – Short life
behavior control
Behavior control
  • (Rod) Brooks – Decompose the problem by task rather than function – Subsumption
  • Advantages of Behavior Based Control
    • Fast behaviors are not slowed down by slow behaviors (act independent of each other)
    • Task Specific so designers can simplify the behavior
alfa a language for action
ALFA – A Language For Action
  • Programming Language to describe reactive behavior-control mechanisms for autonomous robots
  • Consists of Modules connected by Channels
    • Module – Converts inputs to a set of outputs
    • Channel – Dataflow – Data from Modules or sensors
  • Similar to Subsumption
    • No Wires
    • Easier to add modules
    • Provide layers of computational abstraction rather than layers of functionality
tooth overview
Tooth - Overview
  • 30 cm X 20 cm – Indoor Robot
  • 1 Bit Sensors
    • Grippers and rear bumper
    • Infrared Proximity Sensors
  • Analog Sensors
    • Photo Cells (Find Light Beacon)
    • Tachometer on the drive motors
  • Used 3.5kBytes of EEPROM and 100 bytes of RAM
tooth control structure
Tooth – Control Structure
  • Drive Processor/Grasp Processor
  • Bottom Up Design
    • Cooridinating the Drive and Steering Motors
    • Backing up and getting out of endless loops
    • Picking up/Dropping objects – Head to beacon
tooth getting out of loops and dead ends
Tooth – Getting Out of Loops and Dead Ends
  • Unthrash Module
    • Lower priority than obstacle avoidance
    • Counts the number of times the robot changes direction in a certain amount of time and tunrs at a random direction if it thinks it's stuck
  • Dead ends – If the Robot hits a dead end it will back up, then try to go forward. If it hits a wall again, it will back up more the next time.
  • Grasp Module – If it tries too many times to pick up something, it will give up
  • Forward turning radius is different than backwards
tooth results
Tooth - Results
  • No way of searching out objects, just finds them while wandering around
  • Very Robust
  • Could not handle wires, holes or bright lights
rocky iii overview
Rocky III - Overview
  • Demonstrate behavior control could be used in a realistic planetary mission
  • Infrared beacon detector
  • 10 kBytes of RAM
  • Weighs 18kg
rocky iii control structure
Rocky III – Control Structure
  • 3 Layers nearly identical to Tooth
    • Speed and Direction
    • Obstacle Avoidance
    • Sequencer
rocky iii results
Rocky III - Results
  • Very Reliable
    • 90% of the time completes its mission
  • First example of an autonomous that operates in outdoor natural terrain that performs both navigation and manipulation
rocky iv overview
Rocky IV - Overview
  • Chasis is virtually identical to Rocky III
  • Weighs 7.5kg
  • Construction Materials were modified to work in the climate on mars.
  • 1 Master Processor and 3 slave processors
rocky iv status
Rocky IV - Status
  • Not yet complete
  • Every aspect of a Mars mission has been demonstrated
  • Hardware Issues – Activating the rock chipper caused the computer to crash (Obviously not software related)
discussion
Discussion
  • Behavior control succeeds because action selection is not a difficult problem.
  • ALFA code is easy to write, debug, and re-use
  • Other robots were larger because they were required to scale a 1 meter tall objects
  • Few simple sensors work as well as a lot of complex sensors
summary and conclusion
Summary and Conclusion
  • Low power consumption is a necessity
  • Low CPU usage to save power
  • Used a modified version of subsumption
  • ALFA seperates data flow computations from state machine computations
  • As complex as other State of the Art robots