Multiagent task planning based on formal methods has attracted considerable attention due to its ability to handle diverse task specifications and complex systems.However,as the number of agents increases,the planning complexity grows exponentially.Existing search-based methods can only handle medium size fleets while integer program-based algorithms cannot incorporate collaborative actions.To address these issues,this paper proposes a novel planning scheme based on action chains,where tasks are assigned via partial order optimization.Furthermore,an online adaptation and synchronization algorithm is proposed to handle contingent tasks that are generated online and uncertainty during task execution.Extensive numerical simulations are conducted to validate the effectiveness and reliability.
关键词
多智能体任务规划/形式化方法/线性时序逻辑/在线自适应/偏序集
Key words
multiagent task planning/formal method/linear temporal logic/online self-adaptation/partially ordered set
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