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Estimation Of Fields Using Binary Measurements From A Mobile Agent

In this paper we consider the problem of field estimation using a mobile autonomous agent. The agent is equipped with a sensor which can make noisy binary measurements of the field. We model the field as a sum of radial basis functions, whose parameters are then estimated using sequential Monte Carlo (SMC) techniques. We also devise an active sensing mechanism for the agent to adaptively choose its next measurement location, given the information currently collected. Simulation studies illustrate the performance of the proposed algorithms.