Multi-Objective Optimal Trajectory Planning of Space Robot Using Particle Swarm Optimization

  • Authors:

  • Panfeng Huang;Gang Liu;Jianping Yuan;Yangsheng Xu

  • Affiliations:

  • College of Astronautics, Northwestern Polytechnical University, Xi'an, China;Infineon Technologies(Xi'an) Ltd, Xi'an, China;College of Astronautics, Northwestern Polytechnical University, Xi'an, China;Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, China

  • Venue:
  • ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
  • Year:
  • 2008

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Abstract

Space robots are playing significant roles in the maintenance and repair of space station and satellites and other future space services. The motion trajectory planning is a key problem for accomplishing above missions. In order to obtain the high efficiency, safety motion trajectory of space robot, the motion trajectory should be optimized in advance. This paper describes the multi-objective optimization for optimizing the motion trajectory of space robot using a multi-objective particle swarm optimization (MOPSO). In this formulation, the multi-objective function is generated which includes some parameters such as motion time, dynamic disturbance, and jerk, and so on. Then a number of relative parameters can be simultaneously optimized through searching in the parameter space using MOPSO algorithms. The simulation results attest that MOPSO algorithm has satisfactory performance and real value in fact.