An Environmental Potential Field Based RRT Algorithm for UAV Path Planning

Path planning is essential for UAVs to perform some specific missions. In this paper, an environmental potential field based RRT (EPF-RRT) algorithm is proposed to deal with UAVs' path planning problems. The EPF-RRT integrates environmental potential field with the original RRT algorithm, which optimizes the strategy of sampling and expansion. In the EPF-RRT, as the environmental potential field is involved, goal positions generate virtual gravitational force and obstacles are repulsive, the resultant force will guide the RRT grow away from the obstacle and near the target, therefore the efficiency of path planning is greatly improved compared with the RRT. The theoretic analysis and simulation results demonstrate that the proposed EPF-RRT algorithm is characterized by high efficiency, good convergence performance and strong planning ability, which solves the path planning well for UAVs in complicated environments.