Research on Optimal Design of Robotic Arm Joint Angle Path Based on Optimization Algorithms

This paper takes a six-degree-of-freedom robotic arm as the research object and proposes a unified framework for "joint angle path optimization": First, a zero-position precise kinematic model is established using D-H parameters; then, four typical working conditions are sequentially solvedunder only precision constraints, the Whale Optimization Algorithm (WOA) yields joint angles [97.34, 103.88, 13.55, 21.68, 94.19, 89.49] in a single search, with an end-effector error of 2.510 m; when introducing an energy consumption model and targeting both error and energy consumption, the WOA-Monte Carlo hybrid algorithm provides [43.56, 57.16, 38.46, 67.52, 90, 0], with an error of 198 mm and energy consumption of 98.1 J; in obstacle avoidance scenarios, an A* algorithm first plans a collision-free base path, and then the same optimizer is called at each station, resulting in [44.73, 44.72, 38.53, 67.19, 89.62, 0.23], with performance comparable to previous results; for multi-objective grasping tasks, after A* generates a traversal path, each target is independently optimized, achieving a cumulative error of 510 mm and total energy consumption of 119 J. Experiments demonstrate that the integrated method of "D-H kinematics + A* base planning + WOA-MC joint optimization" significantly outperforms baseline approaches in terms of precision, energy consumption, obstacle avoidance, and multi-objective scenarios, showcasing strong potential for engineering applications.