• DocumentCode
    172873
  • Title

    Learning a fast walk based on ZMP control and hip height movement

  • Author

    Shafii, Nima ; Lau, Nuno ; Reis, Luis P.

  • Author_Institution
    LIACC - Artificial Intell. & Comput. Sci. Lab., Portugal
  • fYear
    2014
  • fDate
    14-15 May 2014
  • Firstpage
    181
  • Lastpage
    186
  • Abstract
    The Linear inverted pendulum model is widely used in biped walking approaches. This model assumes that the hip height is fixed while the robot walks. In this paper, the hip height movement, or vertical Center of Mass (CoM) trajectory, is used by a robot to achieve a faster and more stable walk. For the first time, the hip height movement is modeled in a formal way and its parameters are learned. The inverted pendulum model and a numerical approach are used to control the Zero Moment Point (ZMP) for generating a balanced walk. Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is applied to optimize the hip height trajectory and walking parameters with respect to walking speed and stability. Experimental results are achieved on a simulated NAO robot. A comparison of the results of the proposed gait model (and development approach) with those obtained using fixed hip height shows that fixed height walking is slower than variable height walking.
  • Keywords
    covariance matrices; evolutionary computation; humanoid robots; legged locomotion; nonlinear control systems; pendulums; CMA-ES; ZMP control; balanced walk; biped walking approach; covariance matrix adaptation evolution strategy; gait model; hip height movement modelling; hip height trajectory optimization; linear inverted pendulum model; numerical approach; simulated NAO robot; stability; vertical center of mass trajectory; walking parameter optimization; walking speed; zero moment point control; Foot; Hip; Legged locomotion; Mathematical model; Optimization; Trajectory; Biped Walking; Gait Learning; ZMP Control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Robot Systems and Competitions (ICARSC), 2014 IEEE International Conference on
  • Conference_Location
    Espinho
  • Type

    conf

  • DOI
    10.1109/ICARSC.2014.6849783
  • Filename
    6849783