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+# UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown
+
+UFOMap is an efficient probabilistic 3D mapping framework with an explicit representation of unknown space.
+
+![UFOMap visualization](https://user-images.githubusercontent.com/6604166/111369561-7bcabd00-8697-11eb-8145-1409ef9709a0.png)  
+   UFOMap with occupied space as colored voxels and unknown space as white transparent voxels. The free space is not visualized here.
+
+Using UFOMap you will be able to create 3D volumetric maps, containing unknown/free/occupied space, similar to the one below in real-time. The UFOMap maps you create can be used for efficient path/trajectory planning, obstacle avoidance, reconstruction, and more.
+
+![Real-time Volumetric Mapping](https://user-images.githubusercontent.com/6604166/111788476-6c7a8800-88c0-11eb-9592-86609b9eb57c.png)
+   Colored UFOMap constructed in real-time (2 Hz) at 2 mm voxel size.
+
+## Table of Contents
+Please see the [Wiki](https://github.com/UnknownFreeOccupied/ufomap/wiki) for how to install and use UFOMap.
+1. [Setup](https://github.com/UnknownFreeOccupied/ufomap/wiki/Setup)
+2. [Tutorials](https://github.com/UnknownFreeOccupied/ufomap/wiki/Tutorials)
+3. [ROS Tutorials](https://github.com/UnknownFreeOccupied/ufomap/wiki/ROS-Tutorials)
+4. [Advanced ROS Tutorials](https://github.com/UnknownFreeOccupied/ufomap/wiki/Advanced-ROS-Tutorials)
+5. [Performance](https://github.com/UnknownFreeOccupied/ufomap/wiki/Performance)
+6. [Example Outputs](https://github.com/UnknownFreeOccupied/ufomap/wiki/Example-Outputs)
+7. [Data Repository](https://github.com/UnknownFreeOccupied/ufomap/wiki/Data-Repository)
+8. [API](https://github.com/UnknownFreeOccupied/ufomap/wiki/API)
+
+## Credits
+### Paper
+* [IEEE](https://ieeexplore.ieee.org/abstract/document/9158399)
+* [ArXiv](https://arxiv.org/abs/2003.04749)
+### Cite
+If you use UFOMap in a scientific publication, please cite the following paper:
+* Daniel Duberg and Patric Jensfelt, "UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown," in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6411-6418, Oct. 2020, doi: 10.1109/LRA.2020.3013861.
+```latex
+@article{duberg2020ufomap,
+  author={Daniel Duberg and Patric Jensfelt},
+  journal={IEEE Robotics and Automation Letters}, 
+  title={{UFOMap}: An Efficient Probabilistic {3D} Mapping Framework That Embraces the Unknown}, 
+  year={2020},
+  volume={5},
+  number={4},
+  pages={6411-6418},
+  doi={10.1109/LRA.2020.3013861}
+}
+```
+### Videos
+* [YouTube Playlist](https://youtube.com/playlist?list=PLoZnKRp2UVom4bv2fUVXgI5VCbuTrfrU3)