基于改进双向A星和向量场直方图算法的无人机航路规划

现代无人机的行驶环境复杂多变，对无人机的航路规划不仅要求路径最短，同时还要满足实时性以应对突发威胁。提出一种离线规划和在线避障结合的航路规划方法。首先利用改进的双向A*算法对已知环境进行离线规划，并提出基于碰撞检测的动态步长和双向去除冗余点方法，在不影响路径精度的同时，缩短离线规划时间和路径。在无人机按照离线路径行驶过程中，当规划路径中出现突发威胁，利用VFH算法进行实时避障；对避障算法设置子目标，使无人机完成避障后能迅速回到离线轨迹，不影响全局路径的最优性.仿真实验表明，所提方法规划的路径长度短、耗时少，并能有效避开突发威胁，充分结合了双向A*算法路径最优和VFH算法的快速实时避障性的优点。

Path Planning for Unmanned Aerial Vehicles Using Improved Bidirectional A Star and Vector Field Histogram Algorithm

Modern driving environment for unmanned aerial vehicle (UAV) is complicated and changeable,the path of UAV not only requires the shortest length, but also needs to be real-time in response to sudden threat.A kind of path planning method including off-line path planning and online obstacle avoidance was put forward. Firstly,an improved bidirectional A* algorithm was used to plan the path for the known environment,and the methods of dynamic step based on collision detection and removing the redundant point were put forward,which can shorten the planning time and path length without affecting the precision of path planning . While driving,if UAV finds new threats on the off-line,using Vector Field Histogram (VFH) algorithm for real-time obstacle avoidance;and set sub-goals for obstacle avoidance algorithm,to ensure UAV returned to the offline path quickly after completing obstacle avoidance,so that the optimality of the global path will not be affected. The simulation results show that the proposed method can plan a shorter path with less time, and can effectively avoid sudden threat, fully combines the the optimal-path of bidirectional A * algorithm and the advantages of rapid real-time obstacle avoidance of VFH algorithm .