Given a heterogeneous group of robots executing a complex task represented in Linear Temporal Logic, and a new set of tasks for the group, we define the task update problem and propose a framework for automatically updating individual robot tasks given their respective existing tasks and capabilities. Our heuristic, token-based, conflict resolution task allocation algorithm generates a near-optimal assignment for the new task. We demonstrate the scalability of our approach through simulations of multi-robot tasks.
翻译:鉴于由多种机器人组成的小组执行线性时空逻辑中代表的复杂任务,以及该组的新任务,我们定义了任务更新问题,并提议了一个框架,以自动更新各个机器人的任务,并参照其各自的现有任务和能力。我们基于象征性、基于象征性的解决冲突任务分配算法为新任务创造了近乎最佳的任务分配。我们通过模拟多机器人任务来显示我们方法的可缩放性。