基于改进遗传算法的无人机三维航路规划

摘要

Researching UAV path planning can make UAV avoid obstacle during flight.The precision of standard genetic algorithm is low and standard genetic algorithm has poor stability.In order to solve this problem,we researched path planning for UAV on Genetic Algorithm of improved genetic operator.The path was denoted by two-dimension coding in the three-dimensional terrain.The objective function was economizing fuel and avoiding the threaten.Then the fitness function was constructed.The selection and mutation have been improved.The improved selection process can effectively keep the best individual,and the improved the mutation process can produce better individuals.Then we put the improved selection operator and mutation operator into procedure.The simulation result shows that the improved genetic algorithm can converge to the optimal solution and be of stability.So the improved algorithm is an effective and feasible path planning algorithm.%研究无人机航路规划问题,可使无人机在飞行中有效规避障碍物威胁.由于传统的遗传算法在航路规划中寻优精度较低、稳定性较差、迭代速度较慢.为解决上述问题,提出基于改进操作算子的遗传算法,在三维地形条件下,采用二维航路编码方式,将航路燃油最省以及规避威胁作为目标函数,并构造了目标函数的适应度函数,对遗传操作过程中的选择、变异过程进行了改进,改进的选择过程能够有效保留最优个体,改进的变异过程能够产生更优的个体,将改进后的选择算子和变异算子应用到仿真程序中.仿真结果表明,改进后的遗传算法能够快速收敛于最优解且稳定性好,是一种有效可行的航路规划算法.