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Multi-robot online sensing strategies for the construction of communication maps

2019; Springer Science+Business Media; Volume: 44; Issue: 3-4 Linguagem: Inglês

10.1007/s10514-019-09862-3

1573-7527

Alberto Quattrini Li, Phani Krishna Penumarthi, Jacopo Banfi, Nicola Basilico, Jason M. O’Kane, Ioannis Rekleitis, Srihari Nelakuditi, Francesco Amigoni,

Target Tracking and Data Fusion in Sensor Networks

This paper tackles the problem of constructing a communication map of a known environment using multiple robots. A communication map encodes information on whether two robots can communicate when they are at two arbitrary locations and plays a fundamental role for a multi-robot system deployment to reliably and effectively achieve a variety of tasks, such as environmental monitoring and exploration. Previous work on communication map building typically considered only scenarios with a fixed base station and designed offline methods, which did not exploit data collected online by the robots. This paper proposes Gaussian Process-based online methods to efficiently build a communication map with multiple robots. Such robots form a mesh network, where there is no fixed base station. Specifically, we provide two leader-follower online sensing strategies to coordinate and guide the robots while collecting data. Furthermore, we improve the performance and computational efficiency by exploiting prior communication models that can be built from the physical map of the environment. Extensive experimental results in simulation and with a team of TurtleBot 2 platforms validate the approach.