提出了基于遗传算法的URAV航迹规划,将航迹规划的多种约束与算法相融合,综合考虑了多种约束条件对航迹规划的影响。算法采用了改进的航迹极坐标编码方式,算法参数采用了自适应的交叉率和变异率,实现了URAV以最小的被发现概率到达目标点,仿真结果表明该方法是可行而有效的。

The path planning of URAV must take multi-constraint satisfaction as prerequisite, otherwise, the path planned can only be an ideal one, and the application of the flight path will be undesirable. In this paper, a genetic algorithm for path planning of URAV was proposed. Considering the influence of multi-constraints, the genetic algorithm adopted the polar coordinates encoding method, which can embed the path planning constraints into the algorithm model. Adaptive mutation and crossover operators were applied. This method ensures that the URAV should arrive at the target with higher survivability. The simulation results show that this method is feasible and effective for path planning.