基于改进蚁群算法的无人机三维路径规划研究

Research on Path Planning of UAV Based on Improved Ant Colony Algorithm

针对无人机在飞行过程中易受复杂环境与地形信息、确定的和不确定的威胁区等因素影响的情况,为保障无人机的飞行安全,对无人机的路径规划问题进行研究。首先通过栅格化的方法对无人机的飞行环境进行三维建模,并以最短路径为目标,提出一种改进信息素更新规则的蚁群算法,为无人规划出一条安全、最优的飞行路径。最后,采用仿真的方式进行验证,结果表明,与传统算法相比该算法规划出的飞行路径更优,运算时间更短。

In order to ensure the flight safety of the unmanned aerial vehicle, this paper studies the path planning of the unmanned aerial vehicle. It solves the problem that the unmanned aerial vehicle is accessible under complex environment, terrain information, determined or undetermined threats area and other factors during its flight. The flight environment of the unmanned aerial vehicle is modeled in three dimensions by rasterization method. And it uses the shortest path as a goal to improve ant colony algorithm with pheromone update rules. It proposes to plan a safe and optimal flight path for unmanned aerial vehicle. Finally, the simulation results show that the flight path planning by this algorithm is better and the calculation time is shorter than that of the traditional algorithm.