Abstract Mutual knowledge of state information among robots is a crucial requirement for solving distributed control problems, such as coverage control of mobile sensing networks. This paper presents a strategy for exchanging state estimates within a robot team. We introduce a deterministic algorithm that broadcasts estimates of nearby robots more frequently than distant ones. We argue that this frequency should be exponentially proportional to an importance function that monotonically decreases with distance between robots. The resulting location-based algorithm increases propagation rates of state estimates in local neighborhoods when compared to simple flooding schemes.
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