Decentralized localization for dynamic and sparse robot networks

Finite-range sensing and communication are factors in the connectivity of a dynamic mobile robot network. State estimation becomes a difficult problem when communication connections for information exchange between all robots are not guaranteed. This paper presents a decentralized state estimation algorithm guaranteed to work in dynamic networks without connectivity requirements. We show that a robot only needs to consider its own knowledge of network topology in order to produce an estimate equivalent to the centralized state estimate whenever possible, while ensuring the same can be performed by all other robots in the network. Our technique is validated through simulations.