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基于改进蚁群算法的多无人机航路规划研究
引用本文:孟祥恒,王社伟,陶军.基于改进蚁群算法的多无人机航路规划研究[J].计算机仿真,2008,25(11).
作者姓名:孟祥恒  王社伟  陶军
作者单位:空军航空大学航空控制工程系,吉林长春,130022
摘    要:无人机的航路规划研究是无人机任务控制系统的关键技术,在用Voronoi图法对威胁环境建模的摹础上,提出了基于Voronoi图的多行为蚁群算法,增强了蚂蚁之间的协同性,有效解决了可行解的收敛性与多样性之间的矛盾,并对求解过程加入了方向性引导,提高了算法的求解效率.在多机协同方面,利用上述算法分同起止点与不同起止点两种情况对多机协同航路规划进行了仿真,针对得到的多条初始航路,利用协同时间指标对多初始航路进行选择.最后用三次样条方法对协同最优航路进行了平滑处理.

关 键 词:蚁群算法  航迹规划  无人作战飞机

Cooperative Route Planning for UCAVs Using Voronoi Based Multi-Behavior Ant Colony Algorithm
MENG Xiang-heng,WANG She-wei,TAO Jun.Cooperative Route Planning for UCAVs Using Voronoi Based Multi-Behavior Ant Colony Algorithm[J].Computer Simulation,2008,25(11).
Authors:MENG Xiang-heng  WANG She-wei  TAO Jun
Affiliation:MENG Xiang-heng,WANG She-wei,TAO Jun(Department of Aviation Control Engineering,Aviation University of Air Force,Changchun Jilin 130022,China)
Abstract:Route planning plays an important role in Unmanned Air Vehicles' tactical control system.On the basis of Voronoi Diagram,a Voronoi Based Multi-Behavior Ant Colony Algorithm(VBMBACA) is developed.The method enforces the cooperation among the ants,and efficiently resolves the contradiction between diversity and convergence of the solutions.Additionally,direction restriction method is added to VBMBACA to improve the algorithm's efficiency.This algorithm is applied to UCAVs' route planning and enables them to f...
Keywords:Ant colony algorithm  Route planning  UCAV  
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