无人飞行器海上航迹规划差分进化算法研究

为研究海洋环境下的无人飞行器（UAV）航迹规划问题，提出了一种基于差分进化算法（DE）的航迹规划方法。该方法通过对规划环境进行预处理将岛屿处理成地形威胁区，使问题简化为二维平面规划。采用实数编码方式对航迹进行编码，建立了航迹代价函数的数学模型，从航迹质量、算法稳定性和收敛速度3个方面比较了DE与遗传算法（GA）和粒子群优化算法（PSO)的性能。仿真实验结果表明，所提方法能在复杂的海洋环境下为飞行器规划出一条安全的可飞航迹。

Research on Differential Evolution Algorithm for Path Planning for Unmanned Aerial Vehicle in Ocean Environment

To investigate the path of unmanned aerial vehicle(UA) in ocean environment,a method based on the differential evolution(DE)is proposed.It pretreats the planning environment and takes all islands as threatened areas,the path planning problem is simplified as a two-dimensional planning problem.A real number coding is used to represent the candidate paths,and a mathematical model of path cost is established.The performance of differential evolution algorithm is compared with that of genetic algorithm(GA)and particle swarm optimization(PSO)in terms of path quality,robustness and convergence speed.The experimental results demonstrate that the proposed method is able to generate a safe and flyable path for UAV in a complex ocean environment.