• DocumentCode
    2560727
  • Title

    Research on gait planning of artificial leg based on central pattern generator

  • Author

    Jun Xiao ; Su, Jie ; Cheng, Yu ; Wang, Fei ; Xu, Xinhe

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    2147
  • Lastpage
    2151
  • Abstract
    Biped robot with heterogeneous legs (BRHL) is a novel robot model, which consists of an artificial leg and an intelligent bionic leg. The artificial leg is used to simulate the amputeepsilas healthy leg and the bionic leg works as the intelligent artificial limb. To describe the present gait of the healthy leg and make intelligent bionic leg follow the walking of artificial leg in all phases is the target of BRHLpsilas research. So gait planning of artificial leg is the emphasis of BRHLpsilas research. This paper uses the model of central pattern generator (CPG) in the research of artificial legpsilas gait planning from the point of biology. To obtain natural and robust walking pattern, genetic algorithm is used to optimize parameters of the CPG network model and the fitness function is formulated based on zero moment point (ZMP). Simulation results testify the feasibility of this method.
  • Keywords
    artificial limbs; biocybernetics; gait analysis; genetic algorithms; legged locomotion; poles and zeros; CPG network model; artificial leg; biped robot; central pattern generator; fitness function; gait planning; genetic algorithm; heterogeneous legs; intelligent artificial limb; intelligent bionic leg; robot model; zero moment point; Artificial intelligence; Artificial limbs; Biological system modeling; Computational biology; Genetic algorithms; Intelligent robots; Leg; Legged locomotion; Robustness; Testing; CPG; Genetic Algorithm; gait planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597704
  • Filename
    4597704