Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces

Navigation problems expressed via temporal logics show promise for autonomous robot applications due to their versatility. In this paper, we introduce a method for planning with these specifications in uncertain environments that yields guaranteed satisfaction probabilities. We show that point-based value iteration can be combined with probabilistic roadmaps to solve this planning problem over the belief space of the uncertain environment.

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