一种改进的UAV三维航迹实时规划算法

Improved 3-D real-time trajectory planning algorithm for UAV

航迹规划对于战场环境中无人机完成其作战任务具有非常重要的意义.针对真实战场环境中低空无人机的三维航迹实时规划问题,构建了一个更加真实的战场威胁精简模型;提出遗传个体的基因优劣对比度,改进一种共享小生境遗传算法中编码基因的遗传特性.经过改进,增大优化基因的遗传概率,实现提高小生境遗传算法的全局优化能力和收敛速度,增强航迹规划的实时性.对三维数字地形空间进行定长网格编码,将改进的小生境遗传算法应用于三维虚拟战场环境中的无人机航迹规划,实验验证了改进算法的有效性,并能满足在线航迹规划的实时性要求.

It is of vital importance to plan trajectory for unmanned aircraft vehicle（UAV） completing missions in battlefield.A method to address the real-time problem of low-altitude UAV 3-D trajectory planning in realistic battlefield was proposed.Simplified threat models of battlefield were constructed,and an algorithm based on sharing niched genetic algorithm（NGA） was developed by defining the contrast of gene to change gene＇s inheritance characteristic.The improvement made superior genes easy to transmit to the next generation,targeted to accelerate the NGA converging to the global optimum and improve real-time performance of NGA.The algorithm was used to 3-D trajectory planning for UAV in virtual battlefield environments while the 3-D digital terrain space was coded by gridding with constant interval.Experimental results show the effectiveness of the proposed algorithm,and prove it meets the real-time requirement of UAV trajectory planning on-line.