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.%分布式决策是提高群体自主性的关键技术之一.以侦查类无人机(unmanned search aerial vehicles,USAV)和打击类无人机(unmanned combat aerial vehicles,UCAV)执行协同搜索、攻击灰色目标区域问题为背景,建立了一种考虑局部链式通信、无人机飞行性能和任务执行能力等多约束的分布式任务分配模型,基于贝叶斯定理将任务空间的连续/离散不确定量用任务收益值量化描述.然后,提出了一种基于一致性协调算法的在线协同策略,并利用一致协调理论建立了一种冲突调解规则,在此基础上,设计了一种分布式任务分配求解算法,能够实现多USAV, UCAV的协同多任务快速分配.最后,通过数值仿真,验证了本文算法求解不确定空间任务分配问题的可行性和快速性.
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