@inproceedings{
 title = {OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems},
 type = {inproceedings},
 year = {2010},
 id = {eb73020a-2ba4-3122-a5e6-710e7f5bcf3b},
 created = {2022-03-28T09:45:04.439Z},
 file_attached = {true},
 profile_id = {235249c2-3ed4-314a-b309-b1ea0330f5d9},
 group_id = {1ff583c0-be37-34fa-9c04-73c69437d354},
 last_modified = {2022-03-29T08:07:17.620Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {wurmOctoMapProbabilisticFlexible2010},
 source_type = {inproceedings},
 short_title = {OctoMap},
 private_publication = {false},
 abstract = {Abstract—In this paper, we present an approach for modeling 3D environments based on octrees using a probabilistic occupancy estimation. Our technique is able to represent full 3D models including free and unknown areas. It is available as an open-source library to facilitate the development of 3D mapping systems. We also provide a detailed review of existing approaches to 3D modeling. Our approach was thoroughly evaluated using different real-world and simulated datasets. The results demonstrate that our approach is able to model the data probabilistically while, at the same time, keeping the memory requirement at a minimum. I.},
 bibtype = {inproceedings},
 author = {Wurm, Kai M and Hornung, Armin and Bennewitz, Maren and Stachniss, Cyrill and Burgard, Wolfram},
 booktitle = {In Proc. of the ICRA 2010 workshop}
}

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