Distributed Algorithms for Stochastic Source Seeking with Mobile Robot Networks: Technical Report

摘要

Autonomous robot networks are an effective tool for monitoring large-scaleenvironmental fields. This paper proposes distributed control strategies forlocalizing the source of a noisy signal, which could represent a physicalquantity of interest such as magnetic force, heat, radio signal, or chemicalconcentration. We develop algorithms specific to two scenarios: one in whichthe sensors have a precise model of the signal formation process and one inwhich a signal model is not available. In the model-free scenario, a team ofsensors is used to follow a stochastic gradient of the signal field. Ourapproach is distributed, robust to deformations in the group geometry, does notnecessitate global localization, and is guaranteed to lead the sensors to aneighborhood of a local maximum of the field. In the model-based scenario, thesensors follow the stochastic gradient of the mutual information between theirexpected measurements and the location of the source in a distributed manner.The performance is demonstrated in simulation using a robot sensor network tolocalize the source of a wireless radio signal.