• DocumentCode
    2515694
  • Title

    Robot multi-driving controls by cellular neural networks

  • Author

    Kanaya, Mitsuhisa ; Tanaka, Mamoru

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Sophia Univ., Tokyo, Japan
  • fYear
    1994
  • fDate
    18-21 Dec 1994
  • Firstpage
    481
  • Lastpage
    486
  • Abstract
    We propose a novel method based on the local current comparison method for planning the moving paths of a multi-robot and give some simulation results. This method uses an analog resistive network, competitive networks to find the maximum local current, and a digital-type cellular neural network to search the path. The local current comparison method is related to neighbour node analysis, and this method is suitable as the hardware on the analog-digital hybrid chip. Its basic principle is based on analog dynamics, and it makes the plans so fast that plans can be generated in real-time for robots moving comparatively quickly
  • Keywords
    cellular neural nets; cooperative systems; mobile robots; path planning; real-time systems; robot dynamics; simulation; analog dynamics; analog resistive network; analog-digital hybrid chip; cellular neural networks; competitive network; digital-type cellular neural network; hardware; local current comparison method; maximum local current; moving path planning; multi-robot; node analysis; path searching; real-time system; robot multi-driving controls; simulation; Cellular networks; Cellular neural networks; Neural networks; Neurons; Orbital robotics; Path planning; Retina; Robot control; Robot kinematics; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
  • Conference_Location
    Rome
  • Print_ISBN
    0-7803-2070-0
  • Type

    conf

  • DOI
    10.1109/CNNA.1994.381628
  • Filename
    381628