Collaborative planning of formal tasks based on action chains

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.