Abstract

This work proposes an adaptive sampling algorithm for efficient bathymetry mapping of lakes and ponds. The algorithm minimizes the time and energy of the bathymetry mapping task by finding the best sampling locations and avoiding revisiting near the already sampled locations again. This is done by sampling on-the-way so that the variance of previously visited sampling points decrease. The aggressiveness of sampling on-the-way depends on a parameter OSP(on-the-way sampling parameter) and this parameter can be selected based upon the sensing time and other constraints. Simulation results are presented to show that the sampling on-the-way performs far better than the existing GP-UCB technique.

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