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Multi-objective optimal trajectory planning of customized industrial robot based on reliable dynamic identification for improving control accuracy

Renluan Hou (Hangzhou Innovation Institute, Beihang University, Hangzhou, China and Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, China)
Jianwei Niu (State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, China)
Yuliang Guo (Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
Tao Ren (Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
Bing Han (Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
Xiaolong Yu (Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
Qun Ma (Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
Jin Wang (State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, China and Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, China)
Renjie Qi (State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, China and Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 20 June 2022

Issue publication date: 20 September 2022

172

Abstract

Purpose

The purpose of this paper is to enhance control accuracy, energy efficiency and productivity of customized industrial robots by the proposed multi-objective trajectory optimization approach. To obtain accurate dynamic matching torques of the robot joints with optimal motion, an improved dynamic model built by a novel parameter identification method has been proposed.

Design/methodology/approach

This paper proposes a novel multi-objective optimal approach to minimize the time and energy consumption of robot trajectory. First, the authors develop a reliable dynamic parameters identification method to obtain joint torques for formulating the normalized energy optimization function and dynamic constraints. Then, optimal trajectory variables are solved by converting the objective function into relaxation constraints based on second-order cone programming and Runge–Kutta discrete method to reduce the solving complexity.

Findings

Extensive experiments via simulation and in real customized robots are conducted. The results of this paper illustrate that the accuracy of joint torque predicted by the proposed model increases by 28.79% to 79.05% over the simplified models used in existing optimization studies. Meanwhile, under the same solving efficiency, the proposed optimization trajectory consumes a shorter time and less energy compared with the existing optimization ones and the polynomial trajectory.

Originality/value

A novel time-energy consumption optimal trajectory planning method based on dynamic identification is proposed. Most existing optimization methods neglect the effect of dynamic model reliability on energy efficiency optimization. A novel parameter identification approach and a complete dynamic torque model are proposed. Experimental results of dynamic matching torques verify that the control accuracy of optimal robot motion can be significantly improved by the proposed model.

Keywords

Acknowledgements

This work was supported by the Key Research and Development Program of Zhejiang province (Number 2020C01026), the National Natural Science Foundation of China (Number 52175032) and Open Foundation of the Key Laboratory of Advanced Manufacturing Technology of Zhejiang province (Number 2020KF01).

Competing interests: The authors have no competing interests to declare that are relevant to the content of this article.

Citation

Hou, R., Niu, J., Guo, Y., Ren, T., Han, B., Yu, X., Ma, Q., Wang, J. and Qi, R. (2022), "Multi-objective optimal trajectory planning of customized industrial robot based on reliable dynamic identification for improving control accuracy", Industrial Robot, Vol. 49 No. 6, pp. 1156-1168. https://doi.org/10.1108/IR-12-2021-0301

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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