• DocumentCode
    575332
  • Title

    The adjustment system of phase difference using neural oscillator network for a snake-like robot

  • Author

    Matsuo, Takayuki ; Ishii, Kazuo

  • Author_Institution
    Dept. of Control & Inf. Syst. Eng., Kitakyushu Nat. Coll. of Technol., Fukuoka, Japan
  • fYear
    2012
  • fDate
    20-23 Aug. 2012
  • Firstpage
    502
  • Lastpage
    507
  • Abstract
    Robot are expect to be new tools for the operations and observations in the extreme environments where human has difficulties for accessing directly, deep ocean, space, nuclear plants and so on. One of the important matters to realize mobile robots for extreme environments are to establish systems in the movement and their structures which are strong enough to disturbance. A solution for realization an adaptive control system is to learn and imitate biological systems. For example, in the spinal cord of animals, neural oscillator systems called Central Pattern Generator (CPG) are proven to exist and investigated that CPG control rhythmical signals such as swimming pattern, walking locomotion, heart beats, etc. In this paper, an adaptive control system based on the feature of neural oscillators was developed and applied to motion control of a snake-like robot.
  • Keywords
    adaptive control; mobile robots; motion control; neural nets; oscillators; CPG control rhythmical signals; adaptive control system; adjustment system; animals; biological systems; central pattern generator; extreme environments; motion control; neural oscillator network; neural oscillator systems; neural oscillators; phase difference; snake-like robot; spinal cord; Force; Joints; Mathematical model; Oscillators; Robot kinematics; Trajectory; Adaptive control system; Neural oscillator; Snake-like robot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference (SICE), 2012 Proceedings of
  • Conference_Location
    Akita
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-2259-1
  • Type

    conf

  • Filename
    6318491