基于多蚁群系统的多无人机协同目标搜索方法

A Cooperative Target Searching Method Based on Multiple Ant Colony Optimization Algorithm

针对多UAV协同搜索问题,建立了基于搜索概率图的UAV环境信息描述模型,提出了一种基于多蚁群算法的协同目标搜索算法。该算法由多个蚂蚁种群构成,每个蚂蚁种群负责搜索一架无人机的路径。蚂蚁个体在搜索路径时通过其所在群体的信息素的引导以趋向最优路径,同时,受到来自其它种群的信息素的排斥作用进而避免无效搜索。实验结果表明,该方法能有效地实现多UAV之间的协同,实现路径搜索,减少路径交叠,提高了搜索效能。

Considering the cooperative target searching problem,a search probability map based search environment description model is presented,and a cooperative search method based on multiple ant colony optimization algorithm is proposed. This algorithm introduces several different types of ant colonies,and each UAV has an ant colony that searches route for it. Ants are attracted to pheromone of ants in the same colony to search the optimal route,and at the same time,they are repulsed by the pheromone of ants in other colonies to reduce useless search effort. Experimental results demonstrate that this cooperative search method is effective in cooperating multiple UAVs,reducing the overlapping of routes,and improving search effectiveness.