面向多类型目标的多无人机协同搜索

摘要

In the complicated search environment, multi-UAV cooperative search mission may confront with diverse types of targets. Considering the motion features of different types of target, we used a search map method related to probability density function of the targets, and established a reward function appropriate to the coordinated task in order to improve the efficiency of cooperative search. The control architecture combining centralized with distributed control was used, and multi-UAV cooperative search decision making was implemented through predictive control and improved Hungarian algorithm. The decision-making method could improve the search efficiency while avoiding the possible collision of the UAVs. Finally, contradistinctive simulation results demonstrate the validity of the proposed cooperative search strategy.%搜索环境的复杂化使得多无人机( UAV)协同搜索需要面对各种类型的目标。针对各类型目标的运动特征，采用目标存在概率密度相关的搜索图方法，在考虑协同搜索问题特性基础上，建立合理的目标收益函数。采用集中式与分布式相结合的集散式控制框架，结合对搜索图的探测更新，通过预测控制及改进匈牙利算法进行多UAV的协同搜索决策。所用决策方法可在提高搜索效率的同时，有效避免多UAV间可能发生碰撞的问题。最后，通过与传统搜索方法进行仿真对比分析，验证了所提方法的有效性。