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Topology-preserved distorted space path planning

Yangmin Xie (Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China)
Qiaoni Yang (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China)
Rui Zhou (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China)
Zhiyan Cao (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China)
Hang Shi (Department of Automation, Shanghai University, Shanghai, People’s Republic of China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 19 July 2024

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Abstract

Purpose

Fast obstacle avoidance path planning is a challenging task for multijoint robots navigating through cluttered workspaces. This paper aims to address this issue by proposing an improved path-planning method based on the distorted space (DS) method, specifically designed for high-dimensional complex environments.

Design/methodology/approach

The proposed method, termed topology-preserved distorted space (TP-DS) method, mitigates the limitations of the original DS method by preserving space topology through elastic deformation. By applying distinct spring constants, the TP-DS autonomously shrinks obstacles to microscopic areas within the configuration space, maintaining consistent topology. This enhancement extends the application scope of the DS method to handle complex environments effectively.

Findings

Comparative analysis demonstrates that the proposed TP-DS method outperforms traditional methods regarding planning efficiency. Successful obstacle avoidance tasks in the cluttered workspace validate its applicability on a physical 6-DOF manipulator, highlighting its potential for industrial implementations.

Originality/value

The novel TP-DS method generates a topology-preserved collision-free space by leveraging elastic deformation and shows significant capability and efficiency in planning obstacle-avoidance paths in complex application scenarios.

Keywords

Acknowledgements

This research was funded by the National Natural Science Foundation of China under grant number 62173220.

Citation

Xie, Y., Yang, Q., Zhou, R., Cao, Z. and Shi, H. (2024), "Topology-preserved distorted space path planning", Industrial Robot, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IR-02-2024-0049

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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