• DocumentCode
    3044363
  • Title

    Energetically Optimal Gait Transition Velocities of a Quadruped Robot

  • Author

    Shmue, Iris ; Riemer, Raziel

  • Author_Institution
    Dept. of Ind. Eng. & Manage., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    2747
  • Lastpage
    2752
  • Abstract
    Determining gait patterns with low energy consumption per distance traveled are important for increasing robots operation range. These gait patterns, a function of the robot´s speed and structure, are generally determined by optimization processes. In contrast to previous studies that examined the energy consumption of several gait patterns at specific travel velocities, this study presents an optimization process that determines the optimal gait pattern for a range of velocities. In the first part of the study, three optimization methods are compared - the genetic algorithm, the radial-basis function method and the Nelder-Mead simplex. Results indicated that the preferred optimization method is genetic algorithm. In the second part of the study, we reduced the number of optimization variables, using constraints that represent known gait patterns. This led to a reduction of approximately 50% in optimization runtime, while maintaining similar energy consumption per distance as achieved in the first part of the study.
  • Keywords
    gait analysis; genetic algorithms; legged locomotion; optimal control; radial basis function networks; velocity control; Nelder-Mead simplex; energetically optimal gait transition velocities; energy consumption; genetic algorithm; optimal gait pattern; optimization processes; quadruped robot; radial basis function method; robot speed; travel velocities; Genetic algorithms; Joints; Legged locomotion; Linear programming; Optimization methods; dynamic gait; energetic consumption; gait transition; genetic algorithm; optimization; quadruped robot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.469
  • Filename
    6722222