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Time Minimization and Online Synchronization for Multi-agent Systems under Collaborative Temporal Tasks

Zesen LiuMeng GuoZhongkui Li
Aug 2022
摘要
Multi-agent systems can be extremely efficient when solving a team-wide taskin a concurrent manner. However, without proper synchronization, thecorrectness of the combined behavior is hard to guarantee, such as to follow aspecific ordering of sub-tasks or to perform a simultaneous collaboration. Thiswork addresses the minimum-time task planning problem for multi-agent systemsunder complex global tasks stated as Linear Temporal Logic (LTL) formulas.These tasks include the temporal and spatial requirements on both independentlocal actions and direct sub-team collaborations. The proposed solution is ananytime algorithm that combines the partial-ordering analysis of the underlyingtask automaton for task decomposition, and the branch and bound (BnB) searchmethod for task assignment. Analyses of its soundness, completeness andoptimality as the minimal completion time are provided. It is also shown that afeasible and near-optimal solution is quickly reached while the searchcontinues within the time budget. Furthermore, to handle fluctuations in taskduration and agent failures during online execution, an adaptation algorithm isproposed to synchronize execution status and re-assign unfinished subtasksdynamically to maintain correctness and optimality. Both algorithms arevalidated rigorously over large-scale systems via numerical simulations andhardware experiments, against several strong baselines.
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