• DocumentCode
    2098928
  • Title

    Simultaneous design of morphology of body, neural systems and adaptability to environment of multi-link-type locomotive robots using genetic programming

  • Author

    Endo, Ken ; Maeno, Takashi

  • Author_Institution
    Dept. of Mech. Eng., Keio Univ., Yokohama, Japan
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2282
  • Abstract
    In this paper, morphology of body and neural systems that define the locomotion of multilinked locomotive robots that can adapt to changes in environment are designed using the evolutionary computation. The morphology of the body and neural systems have a close relationship to each other. The model of the robot is designed so that the morphology of the body and neural systems emerge simultaneously. The morphology of the body and neural systems are generated using a genetic programming. The tasks are that the robots move on ground including hills of different heights in the two dimensional lateral simulated world under the effect of gravity. The robots are evaluated based both on a moving distance and an efficiency. As a result, various combinations between the morphology of the body and neural systems of the robots were emerged. The evolved robots were able to go over hills which they had not experienced
  • Keywords
    genetic algorithms; mobile robots; neurocontrollers; 2D lateral simulated world; body morphology design; environment adaptability; evolutionary computation; genetic programming; gravity; mobile robots; multilink-type locomotive robots; neural systems design; Actuators; Design methodology; Evolutionary computation; Genetic programming; Humans; Mechanical engineering; Morphology; Orbital robotics; Robot sensing systems; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on
  • Conference_Location
    Maui, HI
  • Print_ISBN
    0-7803-6612-3
  • Type

    conf

  • DOI
    10.1109/IROS.2001.976410
  • Filename
    976410