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为了改进传统的人工势场法不能适应复杂环境、容易陷入最小值和在终点附近徘徊的情况,提出一种基于混沌理论的人工势场法的无人机航迹规划算法。在传统人工势场法原理的基础上,将混沌理论的搜索算法引入人工势场法中的斥力场、引力场的函数公式中,改变了各个障碍物斥力系数和目标点的引力系数,将改变后的系数代入计算,搜索出斥力场和引力场的最优系数组。本算法有如下优点:第一,考虑了障碍物对寻优过程的影响,排除了合力为零的情况。第二,通过迭代的方法,具有适应不同地图的能力。第三,适用于无人机的航迹规划。仿真实验结果和理论分析表明,混沌理论的人工势场法不仅解决了无人机在航迹规划中容易陷入最小值和在终点附近徘徊等问题,而且可以实现无人机在复杂环境下的航迹规划,缩短了飞行成本,节约了计算时间,提高了三维空间无人机航迹规划的速度和精度。
In order to improve the traditional artificial potential field method can not adapt to the complex environment, easy to fall into the minimum and wandering around the endpoint, this paper proposes a tracking algorithm based on the artificial potential field method of chaos theory. Based on the principle of traditional artificial potential field method, the search algorithm of chaos theory is introduced into the function formula of repulsion field and gravitational field in artificial potential field method to change the repulsion coefficient of each obstacle and the gravitational coefficient of the target point, which will change After the coefficient into the calculation, search repulsion and gravitational field of the optimal coefficient set. The algorithm has the following advantages: First, the influence of obstacles on the optimization process is considered, and the situation that resultant force is zero is eliminated. Second, through iterative methods, have the ability to adapt to different maps. Third, it is suitable for UAV flight path planning. Simulation results and theoretical analysis show that the artificial potential field method of chaos theory not only solves the problems that the UAV can easily fall into the minimum value in the trajectory planning and wanders around the terminal point, but also can realize the flight of the UAV in a complex environment Track planning, shortening the flight cost, saving calculation time, improve the speed and accuracy of UAV trajectory planning in three-dimensional space.