基于A~*蚁群算法的无人机航路规划

Path planning of UAVs using A~* ant colony algorithm

针对低空密集复杂环境,在构建环境模型及无人机模型的基础上,提出了一种综合运用A~*算法与蚁群算法的智能航路规划方法。其中A~*算法用于全局航路规划,蚁群算法用于局部路径重规划,利用A~*算法的导向性克服蚁群算法收敛速度慢的缺点,能够使无人机快速到达目标点。仿真结果表明,A~*蚁群算法不仅可以全局引导蚁群算法快速收敛,使无人机快速飞向目标点,同时也可以在局部环境中规避障碍,保证无人机的飞行安全。

To low-altitude and crowded environment,this paper proposed a path planning method which applies A^＊algorithm and ant colony algorithm based on factor models built in this paper. A^＊and ant colony are applied to global and local path planning respectively,which make the UAV reach target position quickly. Simulation results indicate that the A^＊ant colony algorithm can not only guide UAVs to target positions,but also avoid threats,thus ensuring the safety in path planning.