Environment-Adaptive Path Planning Method for Industrial Robot Manipulators

Path planning for multi-degree-of-freedom robot manipulators is the key to realizing automated assembly tasks. However, traditional path search algorithms often fail to converge rapidly to feasible solutions in complex environments. To address this limitation, we propose an environment-adaptive RRT-Connect algorithm (EA-RRT-Connect). The method employs a node safety environment margin assessment to quantify local environmental risk, based on which it dynamically selects parent nodes and adjusts the guidance strategy (including the expansion direction, step size, and node growth constraints), achieving a balance between exploration efficiency and obstacle avoidance reliability. Comparative simulation experiments with RRT, RRT-Connect, and Improved-RRT were conducted in three distinct scenarios. The results indicate that EA-RRT-Connect outperforms baseline methods in planning time, path length, and robustness against local minima.