Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm

Facing the problems of large-scale rapid and disorderly loading, the robotic arm has the problems of large start-stop impact, easy to shake, and reduced production efficiency and service life, this paper proposes a robotic arm motion planning method based on the improved multi-objective algorithm called LNSGA-II. Firstly, the artificial potential field method is used to plan the shortest path without collision, extract the key motion sequences, and establish the multi-objective function to improve the operating efficiency of the robotic arm, the smoothness of the motion trajectory, and the reduction of energy consumption. Then to solve the nonlinear constraints in the multi-objective trajectory planning, the infeasibility degree is designed, and the NSGA-II is improved by using the mutation chaos strategy and the dynamic goal-oriented development strategy. Numerical and trajectory planning experiments are conducted successively with the remaining five well-known multi-objective algorithms, and the experimental results demonstrate the superiority of LNSGA-II. Finally, the digital twin platform of MATLAB-CoppeliaSim-UR16e verifies the effectiveness of the method in real grasping tasks.

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Publication Details

Journal
PLoS ONE
Published
2025-05-29
DOI
https://doi.org/10.1371/journal.pone.0324567
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
1.21

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article

Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm

Yinan Peng, Jianlin Liu, Yanqin Fan
1 citations
PLoS ONE
Robot Manipulation and Learning
1.21
article

Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm

Yinan Peng, Jianlin Liu, Yanqin Fan
article en
1 citations

Abstract

Facing the problems of large-scale rapid and disorderly loading, the robotic arm has the problems of large start-stop impact, easy to shake, and reduced production efficiency and service life, this paper proposes a robotic arm motion planning method based on the improved multi-objective algorithm called LNSGA-II. Firstly, the artificial potential field method is used to plan the shortest path without collision, extract the key motion sequences, and establish the multi-objective function to improve the operating efficiency of the robotic arm, the smoothness of the motion trajectory, and the reduction of energy consumption. Then to solve the nonlinear constraints in the multi-objective trajectory planning, the infeasibility degree is designed, and the NSGA-II is improved by using the mutation chaos strategy and the dynamic goal-oriented development strategy. Numerical and trajectory planning experiments are conducted successively with the remaining five well-known multi-objective algorithms, and the experimental results demonstrate the superiority of LNSGA-II. Finally, the digital twin platform of MATLAB-CoppeliaSim-UR16e verifies the effectiveness of the method in real grasping tasks.

PLoS ONEVol. 20(5)
Guizhou University (CN), Guilin University of Aerospace Technology (CN), Guizhou Education University (CN), Shanghai Medical Information Center (CN), Ministry of Education (RO)
Middle-aged and Young Teachers' Basic Ability Promotion Project of Guangxi
Affordable and clean energy
Openalex Percentile: Top 21%
Robot Manipulation and Learning
1.21
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