基于改进混沌遗传算法的无人机航迹规划

摘要

如何快速地规划出满足约束条件的飞行航迹,是实现无人机自主规划的关键.提出了一种基于混沌遗传算法的航迹规划方法,该方法首先由Voronoi图生成初始航速,然后采用混沌遗传算法在生成的航迹空间中寻优.主要对近年来出现的混沌遗传算法进行了改进以使其更具智能化.该方法采用幂函数载波代替传统混沌优化算法中的线性载波；为进一步提高混沌映射迭代序列的均匀性,提出了确定区间的随机幂指数概念并将其应用到混沌遗传算法中.仿真结果表明,该方法可以提高混沌遗传算法收敛的精确性.%How to plan the flight path quickly which fulfills some constraints is critical for autonomous planning of Unmanned Aerial Vehicles (UAV).This paper proposes a path planning algorithm based on modified chaotic genetic algorithm. First, the Voronoi diagram is utilized to generate the initial paths. Then the optimal path is searched by using improved chaotic genetic algorithm. The chaotic genetic algorithm is improved to make it more intelligent. The method uses a power function as carrier instead of the traditional linear carrier. In order to improve the uniformity of the distribution of chaotic sequence, the concept of random exponent in determinate range is proposed and the concept is applied in the chaos genetic algorithm. Simulation results show that the method can improve the accuracy of the algorithm.