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An adaptive path planning algorithm with singularity consistency for robotic arms

Published online by Cambridge University Press:  03 December 2025

Xianyou Zhong Open the ORCID record for Xianyou Zhong [Opens in a new window] ,
Mengjiao Shen ,
Xiao Lin ,
Chengju Liu  and
Qijun Chen
Xianyou Zhong
Affiliation:
College of Electronic and Information Engineering, Tongji University, Shanghai, China
Mengjiao Shen
Affiliation:
College of Electronic and Information Engineering, Tongji University, Shanghai, China
Xiao Lin
Affiliation:
College of Electronic and Information Engineering, Tongji University, Shanghai, China
Chengju Liu
Affiliation:
College of Electronic and Information Engineering, Tongji University, Shanghai, China
Qijun Chen*
Affiliation:
College of Electronic and Information Engineering, Tongji University, Shanghai, China
*
Corresponding author: Qijun Chen; Email: qjchen@tongji.edu.cn
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Abstract

The study presents a novel approach to address challenges posed by singularities in robotic arm motion, focusing on Cartesian path planning and geometric path adherence. Recognizing limitations in traditional singularity avoidance methods, the research proposes a comprehensive strategy: reconstructing motion patterns in singular regions through singularity-consistent representations, applying arc-length reparameterization to Cartesian geometric paths, and incorporating path curvature as a dynamic weighting factor for sampling interval adjustment. This method achieves a balance between joint velocity smoothness and geometric tracking accuracy in Cartesian space, significantly enhancing the robot’s ability to adhere to prescribed geometric paths, particularly near singularities. Experimental results demonstrate the efficacy of the proposed approach in facilitating smooth singularity transitions, improving joint velocity continuity, and enhancing geometric path adherence. The study contributes to robotic arm path planning by offering a practical solution for applications requiring precise trajectory following and effective singularity handling.

Keywords

singularity consistencypath arc-length parameterizationweights adaptive sampling

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Type
Research Article
Information
Robotica , First View , pp. 1 - 18
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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