Enhanced Artificial Potential Field-based Moving Obstacle Avoidance for UAV in Three-Dimensional Environment

The obstacle avoidance problem plays an essential role in the issues of unmanned aerial vehicle(UAV). An enhanced artificial potential field(EAPF) model is proposed in this paper, considering the three-dimensional vector field and focusing on avoiding the moving obstacle. In the proposed EAPF model, a steering force is designed to change the orientation of UAV's velocity, which can ensure that UAV gets rid of the local minimum situation. And a restoring force considering a slowing down strategy is designed to drag UAV back on the given trajectory. Moreover, an EAPF-based obstacle avoidance(EAPF-OA) algorithm is also proposed to help UAV avoid moving obstacle in flight. Simulation results demonstrate that the proposed EAPF-OA algorithm significantly outperforms the traditional APF-based algorithm on the performance in terms of smoothness, safety and energy consumption.