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Multi-objective optimal trajectory planning for manipulators in the presence of obstacles

Published online by Cambridge University Press:  09 July 2021

Xiaofu Zhang Open the ORCID record for Xiaofu Zhang [Opens in a new window]  and
Guanglin Shi Open the ORCID record for Guanglin Shi [Opens in a new window]
Xiaofu Zhang
Affiliation:
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
Guanglin Shi*
Affiliation:
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
*
*Corresponding author. E-mail: glshi@263.net
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Abstract

This paper presents a trajectory planning method based on multi-objective optimization, including time optimal and jerk optimal for the manipulators in the presence of obstacles. The proposed method generates a trajectory configuration in the joint space with kinematic and obstacle constraints using quintic B-spline. Gilbert–Johnson–Keerthi detecting algorithm is utilized to detect whether there is a collision and obtain the minimum distance between the manipulator and obstacles. The degree of constraint violations is introduced to redefine the Pareto domination, and the constrained multi-objective particle swarm algorithm (CMOPSO) is adopted to solve the time-jerk optimization problem. Finally, the Z-type fuzzy membership function is proposed to select the best optimal solution in the Pareto front obtained by CMOPSO. Test results show the effectiveness of the proposed method.

Keywords

trajectory planningobstacle avoidancemulti-objective particle swarm optimizationQuintic B-spline
Type
Research Article
Information
Robotica , Volume 40 , Issue 4 , April 2022 , pp. 888 - 906
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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