Research on Multi-Objective Trajectory Planning for Industrial Robots Based on Machine Learning

This study proposes a machine learning-based method to address the multi-objective trajectory planning problem for industrial robots. First, the kinematic model of the industrial robot is constructed, and the multi-objective trajectory planning problem is analyzed. Then, a machine learning-based trajectory planning framework is designed, including key steps such as feature engineering, model selection, and training. Subsequently, a multi-objective optimization algorithm is proposed to balance multiple objectives in trajectory planning. Finally, the effectiveness of the proposed method is validated through simulation experiments and practical application cases. The results show that this method significantly improves the efficiency and accuracy of industrial robot trajectory planning, providing a new solution for the field of intelligent manufacturing.