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Effective motion planning of manipulator based on SDPS-RRTConnect

Published online by Cambridge University Press:  04 October 2021

Junxiang Xu Open the ORCID record for Junxiang Xu [Opens in a new window]  and
Jiwu Wang
Junxiang Xu
Affiliation:
School of Mechanical and Electronic Engineering, Beijing Jiaotong University, Beijing, Haidian District, China
Jiwu Wang*
Affiliation:
School of Mechanical and Electronic Engineering, Beijing Jiaotong University, Beijing, Haidian District, China
*
*Corresponding author. E-mails: [email protected], [email protected]
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Abstract

In order to improve the speed of motion planning, this paper proposes an improved RRTConnect algorithm (SDPS-RRTConnect) based on sparse dead point saved strategy. Combining sparse expansion strategy and dead point saved strategy, the algorithm can reduce the number of collision detection, fast convergence, avoid falling into local minimum, and ensure the completeness of search space. The algorithm is simulated in different environments. The results show that in complex environments, the sparse dead point saved strategy plays a good effect. In simple environments, the greedy connection strategy works well. Compared with the standard RRT algorithm, the standard RRTConnect algorithm, and the SDPS-RRT algorithm, the SDPS-RRTConnect algorithm has the shortest planning time, and it is suitable for both simple and complex environments. The 500 experiments show that the algorithm has strong robustness. The actual robot experiments show that the path planned by SDPS-RRTConnect algorithm is effective.

Keywords

motion planningRRTRRTConnectcollision detectionsparse dead points saved
Type
Research Article
Information
Robotica , Volume 40 , Issue 6 , June 2022 , pp. 1855 - 1867
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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