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Nonholonomic motion planning for minimizing base disturbances of space manipulators based on multi-swarm PSO

Published online by Cambridge University Press:  06 November 2015

Qiang Zhang*
Affiliation:
Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Ministry of Education, Dalian, 116622, P. R. China. E-mail: zhoudongsheng@dlu.edu.cn
Lu Ji
Affiliation:
Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Ministry of Education, Dalian, 116622, P. R. China. E-mail: zhoudongsheng@dlu.edu.cn
Dongsheng Zhou
Affiliation:
Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Ministry of Education, Dalian, 116622, P. R. China. E-mail: zhoudongsheng@dlu.edu.cn
Xiaopeng Wei
Affiliation:
Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Ministry of Education, Dalian, 116622, P. R. China. E-mail: zhoudongsheng@dlu.edu.cn College of Computer Science, Dalian University of Technology, Dalian, 116024, P. R. China. E-mail: xpwei@dlut.edu.cn
*
*Corresponding author. E-mail: zhangq@dlu.edu.cn

Summary

Because space manipulators must satisfy the law of conservation of momentum, any motion of a manipulator within a space-manipulator system disturbs the position and attitude of its free-floating base. In this study, the authors have designed a multi-swarm particle swarm optimization (PSO) algorithm to address the motion planning problem and so minimize base disturbances for 6-DOF space manipulators. First, the equation of kinematics for space manipulators in the form of a generalized Jacobian matrix (GJM) is introduced. Second, sinusoidal and polynomial functions are used to parameterize joint motion, and a quaternion representation is used to represent the attitude of the base. Moreover, by transforming the planning problem into an optimization problem, the objective function is analyzed and the proposed algorithm explained in detail. Finally, numerical simulation results are used to verify the validity of the proposed algorithm.

Type
Articles
Copyright
Copyright © Cambridge University Press 2015 

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