Adaptive multiscale sampling in robotic sensor networks

This work focuses on the observation of environmental phenomena that occur as spatial distributions in two and three dimensions, using sensor-enabled mobile vehicle (ground,air or undersea). Algorithms to guide an adaptive exploration of a given region through systematic choice of sampling locations under the constraints imposed by vehicles are presented. Variation sensitive multiresolution sample distributions are achieved through an iterative variation sensitive estimation of the unknown process.

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