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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图生成初始航迹,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 quickly plan the flight path to meet the constraints is the key to the autonomous planning of the UAV. A trajectory planning method based on chaos genetic algorithm is proposed. In this method, the initial trajectory is generated by Voronoi diagram and then chaos genetic algorithm is used to find the optimal trajectory space. The chaos genetic algorithm appearing in recent years is mainly improved to make it more intelligent. In order to further improve the uniformity of the iterative sequences, a power function carrier is used to replace the linear carrier in the traditional chaos optimization algorithm. The concept of random power exponent to determine the interval is proposed and applied to chaos genetic algorithm. Simulation results show that this method can improve the accuracy of the chaos genetic algorithm convergence.