Finding the optimal strategies for robotic patrolling with adversaries in topologically-represented environments

Using autonomous mobile robots to patrol environments for detecting intruders is a topic of increasing relevance for its possible applications. A large part of strategies for mobile patrolling robots proposed so far adopt some kind of random movements. Although these strategies are unpredictable for an intruder, they are not always efficient in getting the patroller a large expected utility. In this paper we propose an approach that considers a model of the adversary in a game theoretic framework to find optimally-efficient patrolling strategies. We show that our approach extends those proposed in literature and we experimentally analyze some of its features.