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OctoMap: an efficient probabilistic 3D mapping framework based on octrees

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Abstract

Three-dimensional models provide a volumetric representation of space which is important for a variety of robotic applications including flying robots and robots that are equipped with manipulators. In this paper, we present an open-source framework to generate volumetric 3D environment models. Our mapping approach is based on octrees and uses probabilistic occupancy estimation. It explicitly represents not only occupied space, but also free and unknown areas. Furthermore, we propose an octree map compression method that keeps the 3D models compact. Our framework is available as an open-source C++ library and has already been successfully applied in several robotics projects. We present a series of experimental results carried out with real robots and on publicly available real-world datasets. The results demonstrate that our approach is able to update the representation efficiently and models the data consistently while keeping the memory requirement at a minimum.

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Notes

  1. http://www.ros.org/wiki/octomap

  2. https://github.com/OctoMap/octomap/archive/v1.5.3.tar.gz

  3. http://ais.informatik.uni-freiburg.de/projects/datasets/octomap

  4. Courtesy of B. Steder, available at http://ais.informatik.uni-freiburg.de/projects/datasets/fr360/

  5. http://www.ros.org/wiki/humanoid_localization

  6. http://www.ros.org/wiki/collider

  7. http://www.ros.org/wiki/3d_navigation and http://www.ros.org/wiki/octomap_server

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Acknowledgments

The authors would like to thank J. Müller, S. Oßwald, R.B. Rusu, R. Schmitt, and C. Sprunk for the fruitful discussions and their contributions to the OctoMap library. This work has been supported by the German Research Foundation (DFG) under contract number SFB/TR-8 and by the European Commission under grant agreement numbers FP7-248258-First-MM and FP7-600890-ROVINA.

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Correspondence to Armin Hornung.

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Hornung, A., Wurm, K.M., Bennewitz, M. et al. OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton Robot 34, 189–206 (2013). https://doi.org/10.1007/s10514-012-9321-0

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