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An Evolutionary Approach to Damage Recovery of Robot Motion with Muscles

  • Siavash Haroun Mahdavi
  • Peter J. Bentley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2801)

Abstract

Robots that can recover from damage did not exist outside science fiction. Here we describe a self-adaptive snake robot that uses shape memory alloy as muscles and an evolutionary algorithm as a method of adaptive control. Experiments demonstrate that if some of the robot’s muscles are deliberately damaged, evolution is able to find new sequences of muscle activations that compensate, thus enabling the robot to recover its ability to move.

Keywords

Genetic Algorithm Shape Memory Alloy Finite State Machine Smart Material Robot Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Siavash Haroun Mahdavi
    • 1
  • Peter J. Bentley
    • 1
  1. 1.Dept. Computer ScienceUniversity College LondonLondonUK

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