基于改进蚁群算法的无人机三维航路规划

3D Route Planning of UAV Based on Improved Ant Colony Algorithm

针对蚁群算法存在收敛速度慢,容易陷入局部最优而导致三维航路规划过程中出现规划时间过长、航路没有达到最优等问题,通过对蚁群算法进行改进,提出了一种天牛须融合改进蚁群的无人机航路规划优化算法,算法通过对蚁群算法的启发函数优化并进行蚁群择优排序,然后融合天牛须算法进行航路规划;将优化算法应用于无人机的三维航路规划中,使规划算法的运行速度更快,无人机的最优航路更短。同时用改进算法与天牛须、蚁群算法的收敛时间、最优路径长度进行对比。仿真实验结果表明,改进算法与另外两种算法相比,在算法收敛度、运行速度方面有明显的提升。

Ant colony algorithm has the problems of slow convergence speed,easy to fall into local optimization,which leads to long planning time and no optimal route in the process of three-dimensional route planning.In this paper,by improving the ant colony algorithm,a route planning optimization algorithm of UAV based on improved ant colony is proposed.The algorithm performs path planning by prioritizing the ant colony and integrating the algorithm.The optimization algorithm is applied to the three-dimensional route planning of UAV,which makes the route planning algorithm run faster and the optimal route of UAV shorter.The convergence time and the optimal path length of the improved algorithm are compared with those of the Tenebrio longissima and ant colony algorithm.The simulation results show that compared with the other two algorithms,the improved algorithm in this paper has a significant improvement in algorithm convergence and running speed.