基于目标信息估计的分布式局部协调任务分配方法

Distributed decision-making is one of the key components to improve the autonomy of robotic agents. Based on the problem of robust task assignment for a fleet of unmanned combat aerial vehicles(UCAV)and unmanned search aerial vehicles(USAV)to targets under environmental uncertainty, a distributed task assignment model which considering multi-constraints such as sparse connected network, UAV performance and task execution ability is given firstly. Bayes law is adopted to handle both continuous uncertainties and discrete uncertainties in mission space, then an on-line cooperative approach based on consensus algorithm is proposed for the given problem, and the decision rules for conflict resolution is given afterwards, and then a distributed task assignment algorithm which can simultaneously allocates UCAVs and USAVs fastly, is proposed. Finally, aspects of feasibility and rapidity of the proposed algorithm is verified according to the simulation results.