ArticlePloS one2025
Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Reinforcement learning-guided multi-objective trajectory planning for obstacle avoidance in robotic manipulators.Scientific reports · 2026Article
- Multi-Objective Trajectory Optimization of a 7-DOF Wiring Robot for Aircraft Harness Layout on Fixture Boards.Sensors (Basel, Switzerland) · 2026Article
- Solving the 3D UAV Path Planning Problem Using an Improved Multi-Leader Multi-Objective Whale Optimization Algorithm.Biomimetics (Basel, Switzerland) · 2026Article
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3 authors.
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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.
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