基于搜索理论的多无人机协同控制方法研究

探讨了多无人机对静止多目标协同搜索问题。运用搜索理论,根据搜索域上的“回报率”状态图,针对多无人机协同控制的搜索规划方法进行了研究。并通过蒙特卡洛仿真,以理论上最优搜索为标准,对协同搜索和随机搜索进行了评估。仿真结果表明,协同搜索相对随机搜索能更有效地利用无人机资源,提高无人机机群的作战效能。

Method of Cooperative Control for UAVs(Uninhabited Air Vehicles) Using Search Theory

We take concepts from search theory~(1]) to help design cooperative search strategy of multiple UAVs for attacking stationary targets.We use the search-theoretic approach based on "rate of return" maps to develop the cooperative search strategy that guides the movement of a group of UAVs so as to get as close to optimal non-implementable search plan as possible.The approach is illustrated by use of a simulation test bed for multiple searching UAVs and Monte Carlo simulation runs to evaluate the cooperative strategy relative to the optimal plan and relative to a noncooperative strategy.Finally we give a simulation example.Numeral results after 100 Monte Carlo runs,as computed by eq.(6) of the full paper,are respectively 415 s for noncooperative strategy,206s for optimal plan,and 153 s for cooperative strategy;these results show preliminarily the usefulness of cooperative strategy.On the other hand,we admit that our research makes the assumption that all information in the war zone are instantly available; this assumption is quite different from the real situation in the war zone;how to develop cooperative strategy for real situation in the war zone needs much further research.