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In this paper, we present a novel multi-resolution approach to efficiently mapping 3D environments. Our representation models the environment as a hierarchy of probabilistic 3D maps, in which each submap is updated and transformed individually. In addition to the formal description of the approach, we present an implementation for tabletop manipulation tasks and an information-driven exploration algorithm for autonomously building a hierarchical map from sensor data. We evaluate our approachdoi:10.1109/iros.2011.6094571 dblp:conf/iros/WurmHHRSKB11 fatcat:zyrjyasui5eltokz73w45kbinu