Dynamic trajectory planning for unmanned aerial vehicle based on sparse A* search and improved artificial potential field
基于稀疏A*搜索和改进人工势场的无人机动态航迹规划

Based on the sparse A* search algorithm for path planning and the improved artificial potential field, we propose a method of dynamic trajectory planning for unmanned aerial vehicle(UAV) in the threat model composed of obstacles with different attributes. This method first builds a grid model of the threat distribution; and then, it makes the global path planning by sparse A* search algorithm according to the static obstacles; Finally, combining the pre-determined route and the dynamic obstacles, UAV can accomplish the dynamic trajectory planning by using the improved artificial potential field. Simulation results indicate that the proposed method can find a global optimal path with the given risk index and achieve a good performance of dynamic obstacle avoidance.