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A Decentralized, On-line Coordination Mechanism for Monitoring Spatial Phenomena with Mobile Sensors

In this paper, we introduce the first on-line, decentralised coordination mechanism for monitoring spatial phenomena with multiple mobile sensors that model the environment using Gaussian processes (GPs). These sensors have their application domain in highly dynamic scenarios, where strict time constraints prohibit path planning in advance, or where the characteristics of the spatial phenomena are unknown a priori. Our coordination mechanism enables the sensors to learn the environmental parameters on-line from their collected observations (and represents them using the GP), and to coordinate their movements to maximise their collective information gain in a decentralised way. We evaluate our algorithm using real-world sensor data collected at the Berkeley Intel Research lab, and demonstrate that a team of 5 mobile sensors equipped with our algorithm monitors the environment with a 51% reduction of Root Mean Squared error compared to a network of fixed sensors that have been deployed using an off-line optimisation algorithm that has complete information of the characteristics of the spatial phenomena.