Distributed processing for multi-robot sampling
In summary, in this chapter we propose a distributed federated filter, and a clustering scheme for the distribution of computational and communication load among N robots performing sampling missions. Estimates of communication and computational load on the robots show that a dramatic reduction can be expected compared to a centralized sampling scheme, while a reduced sampling time in excess of N times can be expected. Further simulations and experiments are needed to verify the efficiency and convergence properties of the distributed filter scheme we propose.
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