Aiming at the problem of unexpected obstacle avoidance during UAV flying, an improved Artificial Potential Field (APF) strategy is proposed.In the process of obstacle avoidance, the obstacle avoidance maneuver angle is used to design the obstacle repulsion coefficient and the velocity control item is added to jointly improve the traditional APF.In comparison to the traditional UAV obstacle avoidance method of setting the target point, this paper uses the virtual submachine to apply the track regression force to the UAV in real time, which ensures that the UAV can return to the original route faster.Furthermore, model prediction is used to adjust the track regression force to avoid the phenomenon of jitter, and then the UAV obstacle avoidance maneuver strategy is designed.The simulation results show that the proposed strategy has higher obstacle avoidance efficiency than the traditional APF method.Finally, as a basic module, the proposed strategy is applied to different complex tasks, which proves that the proposed strategy has high versatility.