Research on motion planning system for wall-climbing mobile manipulator for large steel structures welding operation
Abstract
Purpose
The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility.
Design/methodology/approach
A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling.
Findings
Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions.
Originality/value
The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.
Keywords
Acknowledgements
Funding: This work was supported by the Fundamental Research Funds for the Central Universities, Grant No. 2572023CT15-03.
Citation
Xu, Y., Liu, Y., Liu, X., Wang, B., Zhang, L. and Nie, Z. (2024), "Research on motion planning system for wall-climbing mobile manipulator for large steel structures welding operation", Industrial Robot, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IR-05-2024-0224
Publisher
:Emerald Publishing Limited
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