基于人工免疫克隆选择算法的无人机三维航迹规划

无人机航迹规划作为一个规模大、约束多、指标多的优化问题,其复杂性导致自动规划比较困难。构建了基于局部极坐标的水平航迹控制变量和基于特定平飞段飞行高度的纵向航迹控制变量,以水平航迹控制变量为优化变量,采用分步规划的策略,建立了基于人工免疫克隆选择算法的无人机航迹自动规划模型,该模型能够充分发挥计算机速度快、容量大的特点,能够对基于预处理结果的人工规划方法进行一定程度的改进。仿真结果验证了模型的可行性和有效性。

Three-dimensional planning of unmanned aerial vehicle based on AICS

As an optimization problem with large-scale, multiple constraints and targets, the complex of route planning is very difficult to achieve the automatically planning. Controlvariable of horizontal planning based on local polar coordinates and vertical planning based on the height of the specific horizontal section flight-path are constructed. Theauto route planning model of unmaned aerial vehicle (UAV), using the horizontal flight-path control variable as optimization variable and the step-by-step planning strategy,is established based on the artificial immune clone selection (AICS) algorithm. The model can bring the computer’s characteristics of quick-calculation and high-capacity toplay. Meanwhile, the model can improve the accuracy and efficiency of the manual method based on the pretreatment result. Simulation results prove the feasibility andvalidity of the model.