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Decentralized dynamic trajectory optimization of the coordinated manipulator via analytical reinforcement method

Published online by Cambridge University Press:  23 June 2025

Xingyu Zhang Open the ORCID record for Xingyu Zhang [Opens in a new window] ,
Luchuan Yu Open the ORCID record for Luchuan Yu [Opens in a new window] ,
Shenquan Huang  and
Youzhi Zhang
Xingyu Zhang
Affiliation:
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, People’s Republic of China
Luchuan Yu*
Affiliation:
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, People’s Republic of China
Shenquan Huang
Affiliation:
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, People’s Republic of China
Youzhi Zhang
Affiliation:
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, People’s Republic of China
*
Corresponding author: Luchuan Yu; Email: yulcsdu@foxmail.com
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Abstract

Efficient local trajectory optimization of the coordinated manipulator is a bottleneck task in the narrow feeding scenario. To optimize the trajectory locally and generate collision-free trajectories with local support performance, the analytical reinforcement method is proposed. Firstly, multiple coordinated machines operating in the narrow space are transformed into decentralized dynamic constraints for the target manipulator. Combined with the circle envelope method in the dynamic constraint, the collision-free gradient optimization function determines the support region of the local optimal trajectory. Based on the forward kinematics and inverse kinematics method, the collision-prone pose of the target manipulator outside the support region is analytically optimized. And chi-square distribution further ensures the smooth interpolation of the variable-period trajectory outside the fixed-period support region. For the emergency collision avoidance of the coordinated manipulator in the flexible stamping line, the analytical reinforcement method is successfully verified by generating the collision-free and smooth trajectory. It provides an optimization direction for rapidly improving the work efficiency of multi-machine coordination in the narrow feeding scenario.

Keywords

local trajectory optimizationmulti-machine coordinationanalytical reinforcement methodcollision avoidancestamping line
Type
Research Article
Information
Robotica , First View , pp. 1 - 17
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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