• DocumentCode
    2340561
  • Title

    Multi-objective genetic algorithms for trajectory optimization of space manipulator

  • Author

    Liu, Zhengxiong ; Huang, Panfeng ; Yan, Jie ; Liu, Gang

  • Author_Institution
    Res. Center for Intell. Robot., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    2810
  • Lastpage
    2815
  • Abstract
    This paper propose a multi-objective optimization algorithm to optimize the motion path of space manipulator with multi-objective function. In this formulation, Multi-Objective Genetic Algorithm (MOGA) is used to minimize the multi-objective function. The planning procedure is performed in joint space and with respect to all constraints, such as joint angle constraints, joint velocity constraints, torque constraints.We use a MOGA to search the optimal joint inter-knot parameters in order to realize the optimal motion trajectory for space manipulator. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation results test that the proposed multi-objective genetic algorithm has satisfactory performance.
  • Keywords
    genetic algorithms; manipulators; minimisation; motion control; optimal control; path planning; position control; torque control; velocity control; genetic algorithm; joint angular velocity; multiobjective genetic algorithm; optimal joint inter-knot parameter; space manipulator; trajectory optimization; Genetic algorithms; Intelligent robots; Manipulator dynamics; Motion planning; Orbital robotics; Path planning; Space missions; Space technology; Torque; Trajectory; Multi-objective genetic algorithm; Space manipulator; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138722
  • Filename
    5138722