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Information-Theoretic Approach to Navigation for Efficient Detection and Classification of Underwater Objects
This paper addresses an autonomous exploration problem in which a mobile sensor, placed in a previously unseen search area, utilizes an information-theoretic navigation cost function to dynamically select the next sensing action, i. e., location from which to take a measurement, to efficiently detect and classify objects of interest within the area.
Bayesian Learning of Occupancy Grids
Occupancy grids encode for hot spots on a map that is represented by a two dimensional grid of disjoint cells.
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