Autonomous Path Planning Based on Artificial Potential Field for Waypoint Tracking and Collision Avoidance

Abstract

In this thesis, we propose a waypoint tracking scheme with a collision-avoidance system using the artificial potential field (APF) with speed planning. It is shown that there is little literature about the combination work of waypoint tracking and APF-based local path planner. We present a new path planning method to smoothly join the local path predicted by APF to avoid obstacles and the path given by irregular waypoints to eliminate severe yawing of the heading angle of the vehicle. The proposed speed planning combined with APF effectively prevents possible excessive tire slip angle of the vehicle driving at high speed. The simulation results show that the proposed path planning algorithm with speed planning is effective in collision avoidance with static and/or dynamic obstacles for the waypoint tracking scenario. This proposed method is validated with the vehicle dynamic lateral motion model in MATLAB/Simulink and CarSim.