• DocumentCode
    1644258
  • Title

    Optical tracking system for automatic guided vehicles using cellular neural networks

  • Author

    Eröss, Gy ; Boros, T. ; Kiss, A. ; Radványi, A. ; Roska, T. ; Bitò, J. ; Vass, J.

  • Author_Institution
    Tungsram TH Co. Ltd., Budapest, Hungary
  • fYear
    1992
  • Firstpage
    216
  • Lastpage
    221
  • Abstract
    A method for the path-control of automated guided vehicles (AGVs) in computer integrated manufacturing (CIM) systems that combines the flexibility and easy installation of optical methods with the simplicity and robustness of the inductive method is proposed. Using a new computing paradigm, the cellular neural network (CNN), and a related device, the VLSI CNN chip, a very high speed solution that is less expensive than the conventional methods can be achieved. This AGV control complies with the requirements of CIM systems. Further advantages of the proposed system are as follows: fault tolerance and the ability to give instructions along the path, and the use of a simple local control
  • Keywords
    VLSI; automatic guided vehicles; cellular arrays; computer integrated manufacturing; computerised materials handling; image processing; neural chips; neural nets; AGVs; CIM; VLSI CNN chip; automatic guided vehicles; cellular neural networks; computer integrated manufacturing; fault tolerance; inductive method; optical tracking system; path-control; Cellular neural networks; Computer integrated manufacturing; Computer networks; Control systems; High speed optical techniques; Integrated optics; Optical computing; Robustness; Vehicles; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-0875-1
  • Type

    conf

  • DOI
    10.1109/CNNA.1992.274366
  • Filename
    274366