摘要： 用文化基因算法求解无人布雷机航路规划问题，设计无人布雷机的航路规划仿真系统。以粒子群优化算法为主搜索策略，利用单向信息共享机制提高收敛速度。采用模拟退火的方法进行局部修正，以减小局部极值的影响。利用Visual C++中MFC编制OpenGL程序的方式模拟飞行过程，通过Matlab中的GUI建立三维航路规划系统仿真平台，实现三维航路可视化。

关键词: 无人机, 航路规划, 文化基因算法, 粒子群优化算法, 布雷

Abstract: In order to solve the air route plan problem of unmanned mine-laying aerial vehicle, the Memetic algorithm is adopted and simulated. The Particle Swarm Optimization(PSO) is selected as the main planning method while the simulated annealing algorithm is applied in the local search to complete the whole process of route planning. Taking the practical necessary of mining, the route plan simulation system of UMAV is designed. By OpenGL programmer in MFC of the Visual C++, the process of flying is simulated, and a 3-D route planning simulation platform is established by GUI in Matlab.

Key words: Unmanned Aerial Vehicle(UAV), air route plan, Memetic algorithm, Particle Swarm Optimization(PSO) algorithm, mine-laying

中图分类号: 

• TP391.9