Combining Coordination and Independent Coverage in MultiRobot Graph Patrolling

Carlos Diaz Alvarenga, Nicola Basilico, Stefano Carpin

Abstract: Graph patrolling algorithms provide effective strategies for coordinating mobile robots in the context of autonomously surveilling valuable assets. Optimizing patrolling strategies often aims to minimize the time between subsequent visits to a vertex, a measure known in the literature as idleness. In the domain of multi-robot patrolling, two approaches have received the most attention so far. The first involves coordinating all robots to follow a shared patrolling strategy covering the entire graph, while the second approach partitions the environment into disjoint areas that are then assigned to individual robots. Starting from these existing solutions, this paper introduces a new method that bridges these two complementary approaches. Our technique splits the vertices of the graph into a partition that includes a shared portion of the environment patrolled collectively by all robots, along with disjoint areas allocated exclusively to individual robots. This problem is formulated in terms of minimizing the maximum weighted idleness of the graph and is shown to be NP-hard. We then describe an exact solution for the problem and propose various heuristics to efficiently compute solutions for large problem instances. We evaluate and compare the proposed techniques in simulation and demonstrate that, in most cases, our methods produce better patrolling strategies when compared to classic solutions. Moreover, for small problem instances where the exact solution can be found, we show that our proposed heuristic has a competitive performance ratio.