Octrees for faster isosurface generation
ACM Transactions on Graphics (TOG)
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Efficient high quality rendering of point sampled geometry
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments
International Journal of Robotics Research
Mapping and Exploration of Complex Environments Using Persistent 3D Model
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
6D SLAM—3D mapping outdoor environments: Research Articles
Journal of Field Robotics
Scan registration for autonomous mining vehicles using 3D-NDT: Research Articles
Journal of Field Robotics - Special Issue on Mining Robotics
3D Perception and Environment Map Generation for Humanoid Robot Navigation
International Journal of Robotics Research
The New College Vision and Laser Data Set
International Journal of Robotics Research
3D mapping with multi-resolution occupied voxel lists
Autonomous Robots
Efficient sparse voxel octrees
Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games
Robotics and Autonomous Systems
Manipulator and object tracking for in-hand 3D object modeling
International Journal of Robotics Research
KinectFusion: Real-time dense surface mapping and tracking
ISMAR '11 Proceedings of the 2011 10th IEEE International Symposium on Mixed and Augmented Reality
Octree-based point-cloud compression
SPBG'06 Proceedings of the 3rd Eurographics / IEEE VGTC conference on Point-Based Graphics
Scalable real-time volumetric surface reconstruction
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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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.