A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Computing standard deviations: accuracy
Communications of the ACM
Updating formulae and a pairwise algorithm for computing sample variances
Updating formulae and a pairwise algorithm for computing sample variances
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scan registration for autonomous mining vehicles using 3D-NDT: Research Articles
Journal of Field Robotics - Special Issue on Mining Robotics
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Fast point feature histograms (FPFH) for 3D registration
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Robust 3D-mapping with time-of-flight cameras
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
International Journal of Robotics Research
Real-time dense geometry from a handheld camera
Proceedings of the 32nd DAGM conference on Pattern recognition
Online loop closure for real-time interactive 3D scanning
Computer Vision and Image Understanding
Data-Parallel Octrees for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
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
RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
International Journal of Robotics Research
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
IEEE Transactions on Robotics
DTAM: Dense tracking and mapping in real-time
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Building consistent models of objects and scenes from moving sensors is an important prerequisite for many recognition, manipulation, and navigation tasks. Our approach integrates color and depth measurements seamlessly in a multi-resolution map representation. We process image sequences from RGB-D cameras and consider their typical noise properties. In order to align the images, we register view-based maps efficiently on a CPU using multi-resolution strategies. For simultaneous localization and mapping (SLAM), we determine the motion of the camera by registering maps of key views and optimize the trajectory in a probabilistic framework. We create object models and map indoor scenes using our SLAM approach which includes randomized loop closing to avoid drift. Camera motion relative to the acquired models is then tracked in real-time based on our registration method. We benchmark our method on publicly available RGB-D datasets, demonstrate accuracy, efficiency, and robustness of our method, and compare it with state-of-the-art approaches. We also report on several successful public demonstrations where it was used in mobile manipulation tasks.