无人机全局航路规划技术仿真

Simulation of Global Optimal Flight Path Planning for UAV

针对不同强度威胁源构成的飞行环境,提出了一种基于人工势场法和遗传算法相结合的无人机全局航路规划方法。该方法对威胁进行Delaunay三角网划分,按照穿越三角形边的方向及顺序设计了一种二进制编码方法;把威胁当作斥力源,初始路径当作质量-弹簧链路,求解链路的受力方程,得到该穿越方式下的局部最佳航路;最后利用遗传算法获得威胁网络下的全局最优解。经过三种不同参数情况下的计算机仿真,结果证明该方法能够得到给定的威胁指标下的全局最优航路。

based on the artificial potential field and genetic algorithms, a method of flight path planning for UAV in the threat network was proposed. The threats were divided by Delaunay triangulation. According to the passing directions and sequence of the triangles＇ lines, a binary coding method was designed. Then the threats were taken as repulsion sources and the steady-state result of the differential equations is the optimal flight path of the code array. The global optimal flight path, could be obtained by using genetic algorithms. Simulation results show that the method is effective.