Distributed Estimation of Scalar Fields with Implicit Coordination

Motivated by our ongoing work in robotics for precision agriculture, in this work we consider the problem of estimating a scalar field using a team of robots collecting samples and subject to a travel budget. Our fully distributed method leverages the underlying properties of Gaussian Process regression to promote dispersion using minimal information sharing. Extensive simulations demonstrate that our proposed solution outperforms alternative approaches.