• DocumentCode
    1871634
  • Title

    Evolving sufficient robot controllers

  • Author

    Lund, Henrik Hautop ; Hallam, John

  • Author_Institution
    Dept. of Artificial Intelligence, Edinburgh Univ., UK
  • fYear
    1997
  • fDate
    13-16 Apr 1997
  • Firstpage
    495
  • Lastpage
    499
  • Abstract
    Different methods exist for reducing the time consumption in evolutionary robotics experiments. One is to use simulations, while another is to evolve controllers that are no more complex than task fulfilment requires. Behaviors such as exploration and homing, that seemingly demand a complex control system, only require a perceptron that connects a robot´s sensors to its motors. This is shown by evolving such neurocontrollers for the Khepera robot. An exploitation of the robot´s perception of the environment´s geometrical shape allows the robot to encode time, even though explicitly it is not presented with the time and there are no recurrent connections in the neurocontroller
  • Keywords
    genetic algorithms; mobile robots; neurocontrollers; optimal control; perceptrons; temporal reasoning; Khepera robot; environment geometrical shape perception; evolutionary robotics; exploration; homing; mobile robots; neurocontrollers; perceptron; robot sensor-motor connection; simulations; sufficient robot controllers; temporal encoding; time consumption; Artificial intelligence; Control systems; Convergence; HTML; Mobile robots; Neurocontrollers; Robot control; Robot sensing systems; Shape; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1997., IEEE International Conference on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    0-7803-3949-5
  • Type

    conf

  • DOI
    10.1109/ICEC.1997.592361
  • Filename
    592361