基于蚁群算法的最小代价航迹规划仿真

在大比例尺地图的路径规划中，由于飞行器全局航迹规划需要计算机存储的栅格点数量巨大，存在维数爆炸问题，使得航迹解算计算量激增，因此提出1种改进的蚁群算法，将栅格由大及小进行划分，利用大栅格为飞行器选择相对平滑和离散度低的飞行地形，利用小栅格为飞行器提供相对精确的全局飞行航迹，将栅格带所有栅格的代价之和作为航迹代价，从而选出1条航迹代价最小的路径．该算法将蚁群算法的信息素更新机制更加合理地应用到航迹规划中．仿真结果表明，该方法能解决航迹维数解算问题，可以将一系列栅格点组成的路径点集合为最优解，为飞行器提供最优航迹规划路径．

Simulation on minimum cost trajectory planning based on ant colony algorithm

In path planning of large-scale map,the global trajectory planning of aircraft requires computers to store a huge number of grid points.So the dimension explosion problem exists in it and the cost of trajectory computation is huge.An improved ant colony algorithm is proposed:the grids are divided from big to small;the big grids are used to choose relatively smooth and low dispersion terrain for aircraft;the small grids are used to provide relatively accurate track of whole flight for aircraft;and the sum of...