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.