改进A*与IDWA的无人机动态航迹规划融合算法OA

In order to find the best algorithm for UAV(unmanned aerial vehicle)trajectory planning and effectively solve the phenomenon that the A* algorithm has multiple turning points and redundant trajectory lengths in the two-dimensional plane,a fusion algorithm for UAV dynamic trajectory planning is proposed that combines the improved A* algorithm and the improved dynamic window approach(IDWA)method.The A* algorithm is improved based on extended neighborhood search.From three aspects:kinematic model construction,velocity sampling,and evaluation function improvement,the improved A* algorithm and IDWA method are fused together to obtain a new fusion improved algorithm.Finally,static obstacles and dynamic obstacles are used to verify the application performance of the fusion improved algorithm.The results show that when there are static obstacles,the UAV designed using the improved fusion algorithm takes less time to plan its path and has a shorter track length.In the case of dynamic obstacles,the UAV can automatically adjust its course at the starting point and effectively avoid dynamic obstacles,confirming the application value of the improved A* and IDWA fusion algorithm in UAV trajectory planning.