无人机由于其高可控性、高机动性、零伤亡等优点，在边防巡逻、抢险救灾、侦察打击等定点侦察类任务中发挥越来越重要的作用。研究设计复杂环境下的定点侦察任务航线智能规划系统，对提高作业安全性和有效性具有重要意义。在对定点侦察类任务分析后，进行任务拆解。分别对二维避障航线规划、三维避障航线规划、多目标点遍历三部分进行算法设计。针对A *算法大范围搜索效率低的问题，提出了剪枝和节点分代搜索方法。针对多点遍历存在的组合爆炸问题，提出了自适应遗传算法的解决方案。最后结合具体的仿真实例，验证了规划系统性能。结果表明，通过无人机定点侦察任务智能航线规划系统设计，可以快速实现对多目标点生成避障、遍历航线，提高飞机任务执行效率和安全性。

Because of its high controllability, high mobility, zero casualties and other advantages, UAV plays an increasingly important role in such fixed-point reconnaissance missions as Border Patrol, disaster rescue, reconnaissance and strike. It is important to study and design the route intelligent planning system of fixed-point reconnaissance mission in complex environment to improve the security and effectiveness of the operation. After analyzing the fixed-point reconnaissance task, the task was disassembled. Two-dimensional obstacle avoidance route planning, three-dimensional obstacle avoidance route planning and multi-objective point traversal were designed respectively. Aiming at the low efficiency of A * algorithm in large-scale search, a pruning and node generation search method was proposed. An adaptive genetic algorithm (AGA) was proposed to solve the combination explosion problem of multi-point ergodic. Finally, the performance of the planning system was verified by a concrete simulation example. The results show that through the design of the intelligent route planning system for unmanned aerial vehicle fixed - point reconnaissance missions, it is possible to quickly generate obstacle avoidance and traverse routes for multiple target points, thereby improving the efficiency and safety of aircraft mission execution.