Dynamic Environment Adaptive Path Planning for Mobile Robots: A Hybrid Enhanced Path‐Planning Approach

ABSTRACT With the rapid advancement of mobile robotics, the demand for safe and efficient path planning has become increasingly prominent. This research aims to address the challenges of path redundancy and the lack of stable obstacle avoidance strategies encountered by mobile robots during path planning in dynamic environments. A novel hybrid enhanced path‐planning algorithm is proposed, which integrates obstacle information, robot safety data, path‐simplification techniques, and dynamic‐obstacle avoidance strategies. By combining global and local path planning and introducing a path evaluation system based on robot status and dynamic‐obstacle motion information, the algorithm achieves efficient and flexible path planning. The effectiveness and feasibility of the algorithm are validated through simulation experiments and real‐world testing. The results demonstrate that the algorithm can achieve safe and efficient path planning under different speeds and dynamic‐obstacle scenarios, significantly reducing the frequency of path switching and waiting times, thus enhancing the efficiency and autonomy of the robot's actual scene navigation. In the experimental scene, the overall travel time is saved by 8.3%, the traffic obstacle area time is saved by 48.9%, and the obstacle avoidance route is stable and efficient. Compared with the current advanced algorithm, the proposed algorithm can improve the driving efficiency of the robot by more than 12%, and the robot's behaviour is more secure in the face of dynamic obstacles. This research provides an effective solution for mobile robot path planning in complex environments, with significant theoretical and practical implications.