Behavior Control for Robotic Exploration of Planetary Surfaces

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Behavior Control for Robotic Exploration of Planetary Surfaces

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Behavior Control for Robotic Exploration of Planetary Surfaces ... Tachometer on the drive motors. Used 3.5kBytes of EEPROM and 100 bytes of RAM ... –

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Title: Behavior Control for Robotic Exploration of Planetary Surfaces


1
Behavior Control for Robotic Exploration of
Planetary Surfaces
  • Written by Erann Gat, Rajiv Desai, Robert Ivlev,
    John Loch and David P Miller
  • Presented By Tony Morelli
  • 9/30/2004

2
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.

3
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

4
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

5
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

6
ALFA Code Sample

7
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

8
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

9
Tooth Control Structure
10
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

11
Tooth - Results
  • No way of searching out objects, just finds them
    while wandering around
  • Very Robust
  • Could not handle wires, holes or bright lights

12
Rocky III - Overview
  • Demonstrate behavior control could be used in a
    realistic planetary mission
  • Infrared beacon detector
  • 10 kBytes of RAM
  • Weighs 18kg

13
Rocky III Control Structure
  • 3 Layers nearly identical to Tooth
  • Speed and Direction
  • Obstacle Avoidance
  • Sequencer

14
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

15
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

16
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)

17
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

18
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

19
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