A Distributed Multi-Robot Adaptive Sampling Scheme for the Estimation of the Spatial Distribution in Widespread Fields

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Monitoring widespread environmental fields is undoubtedly a practically important area of research with many complex and challenging tasks. It involves the building of models of the fields or natural phenomena to be monitored, the estimation of the spatio-temporal distribution of a variety of environmental parameters of interest, such as moisture or salinity in a crop field, or the spatial distribution of vital natural resources such as oil and gas, etc. Sampling, a key operation of the monitoring process, is a broad methodology for gathering statistical information about the phenomenon or environmental variable, being monitored. To efficiently monitor widespread fields and estimate the spatio-temporal distribution of some particular environmental variable, calls for the use of a sampling strategy can fuse information from different scales of sensors.