Autonomous robot networks are an effective tool for monitoring large-scale environmental fields. This paper proposes distributed control strategies for localizing the source of a noisy signal, which could represent a physical quantity of interest such as magnetic force, heat, radio signal, or chemical concentration. We develop algorithms specific to two scenarios: one in which the sensors have a precise model of the signal formation process and one in which a signal model is not available. In the model-free scenario, a team of sensors is used to follow a stochastic gradient of the signal field. Our approach is distributed, robust to deformations in the group geometry, does not necessitate global localization, and is guaranteed to lead the sensors to a neighborhood of a local maximum of the field. In the model-based scenario, the sensors follow a stochastic gradient of the mutual information (MI) between their expected measurements and the expected source location in a distributed manner. The performance is demonstrated in simulation using a robot sensor network to localize the source of a wireless radio signal.
Distributed Algorithms for Stochastic Source Seeking With Mobile Robot Networks
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received January 31, 2014; final manuscript received June 10, 2014; published online October 21, 2014. Assoc. Editor: Dejan Milutinovic.
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Atanasov, N. A., Le Ny, J., and Pappas, G. J. (October 21, 2014). "Distributed Algorithms for Stochastic Source Seeking With Mobile Robot Networks." ASME. J. Dyn. Sys., Meas., Control. March 2015; 137(3): 031004. https://doi.org/10.1115/1.4027892
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