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Biological Cybernetics

, Volume 99, Issue 3, pp 185–196 | Cite as

Application of chaotic dynamics in a recurrent neural network to control: hardware implementation into a novel autonomous roving robot

  • Yongtao LiEmail author
  • Shuhei Kurata
  • Shogo Morita
  • So Shimizu
  • Daigo Munetaka
  • Shigetoshi Nara
Original Paper

Abstract

Originating from a viewpoint that complex/chaotic dynamics would play an important role in biological system including brains, chaotic dynamics introduced in a recurrent neural network was applied to control. The results of computer experiment was successfully implemented into a novel autonomous roving robot, which can only catch rough target information with uncertainty by a few sensors. It was employed to solve practical two-dimensional mazes using adaptive neural dynamics generated by the recurrent neural network in which four prototype simple motions are embedded. Adaptive switching of a system parameter in the neural network results in stationary motion or chaotic motion depending on dynamical situations. The results of hardware implementation and practical experiment using it show that, in given two-dimensional mazes, the robot can successfully avoid obstacles and reach the target. Therefore, we believe that chaotic dynamics has novel potential capability in controlling, and could be utilized to practical engineering application.

Keywords

Chaotic dynamics Autonomous robot Recurrent neural network Hardware implementation 

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Yongtao Li
    • 1
    Email author
  • Shuhei Kurata
    • 1
  • Shogo Morita
    • 1
  • So Shimizu
    • 1
  • Daigo Munetaka
    • 1
  • Shigetoshi Nara
    • 1
  1. 1.Graduate School of Natural Science and TechnologyOkayama UniversityOkayamaJapan

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