Distributed Task Allocation and Planning Under Temporal Logic and Communication Constraints

It is challenging to coordinately allocate and plan the tasks of a heterogeneous multi-agent system in a shared workspace. It can be even more challenging if the agents are subject to limited communication capability (i.e., exchange information with nearby agents only) and complex tasks with temporal and logic constraints. Motivated by these practical challenges, a distributed task allocation and planning method is developed, in which each agent communicates with neighboring agents about the task information (i.e., the preference of sub-tasks to be executed and the estimated task completion time) and predicts the task information of agents out of the communication range. Based on the collected task information, each agent can independently make conflict-free planning to improve the execution efficiency of the task. Rigorous analysis shows that the generated plan is guaranteed to be conflict free and numerical experiments demonstrate the effectiveness of the planned tasks.