针对多旋翼无人机的编队动态航路规划问题, 提出一种蚁群算法和快速扩展随机树RRT算法相结合的改进混合算法。首先利用蚁群算法离线搜索全局航路代价最小的初始航路, 在局部航路规划中提出“协同避障—重构”策略, 同时运用改进RRT算法实时修正几何航路, 使机群满足时间协同约束绕过静态威胁源和突发障碍物, 编队飞行至目的地。仿真结果表明, 提出的改进混合算法和策略能有效规划无人机动态无碰航路, 相较普通RRT算法, 航路最优性及局部航路在线搜索速率得到明显提升。

To solve the problem of dynamic route planning for multi-rotor Unmanned Aerial Vehicle (UAV) formation, an improved hybrid algorithm combining ant colony algorithm with Rapidly-exploring Random Tree (RRT) algorithm was proposed.Firstly, the ant colony algorithm was used to search the original global route with the lowest cost, and the “cooperative avoidance-reconstruction” strategy was proposed in the local route planning.Then the improved RRT algorithm was used to modify the geometric route in real time, thus the UAV formation could avoid the static threats and unexpected obstacles and fly to the destination while satisfying the time constraints.The simulation results show that:1) The improved hybrid algorithm and strategy can implement the dynamic route planning for UAVs effectively;and 2） Compared with the common RRT algorithm, the optimality of the overall route and the online search rate of the local route are improved significantly.