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We present an algorithm to explore an orthogonal polygon using a team of $p$robots. This algorithm combines ideas from information-theoretic explorationalgorithms and computational geometry based exploration algorithms. We showthat the exploration time of our algorithm is competitive (as a function of$p$) with respect to the offline optimal exploration algorithm. The algorithmis based on a single-robot polygon exploration algorithm, a tree explorationalgorithm for higher level planning and a submodular orienteering algorithm forlower level planning. We discuss how this strategy can be adapted to real-worldsettings to deal with noisy sensors. In addition to theoretical analysis, weinvestigate the performance of our algorithm through simulations for multiplerobots and experiments with a single robot.

Combining Geometric and Information-Theoretic Approaches for Multi-Robot Exploration