Mobile Robot Path Planning Based on A-Star Algorithm and Artificial Potential Field Method for Autonomous Navigation

This paper presents a hybrid path-planning algorithm that combines both global and local planning techniques. An offline global path planning approach based on the A -Star graph search algorithm is used to find the optimal path from the start to the goal. However, A -Star has some limitations, such as a lack of smoothness, lower safety margins, and an inability to adapt to dynamic environments. To address these issues, we propose integrating an online local path planning method based on the Artificial Potential Field (APF) for real-time obstacle avoidance. Simulation results demonstrate the effectiveness of the hybrid approach, guiding the mobile robot along the optimal global path while ensuring the locally gener-ated trajectory is smooth enough for execution by the controller. The results also show improved navigation performance, with enhanced efficiency and safety due to the hybrid algorithm.