SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
A simple method for box-sphere intersection testing
Graphics gems
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Real-Time Collision Detection (The Morgan Kaufmann Series in Interactive 3-D Technology) (The Morgan Kaufmann Series in Interactive 3D Technology)
Robotic Grasping of Novel Objects using Vision
International Journal of Robotics Research
Towards semantic maps for mobile robots
Robotics and Autonomous Systems
Towards 3D Point cloud based object maps for household environments
Robotics and Autonomous Systems
On fast surface reconstruction methods for large and noisy point clouds
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Object recognition and full pose registration from a single image for robotic manipulation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Depth-encoded hough voting for joint object detection and shape recovery
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Combined 2D-3D categorization and classification for multimodal perception systems
International Journal of Robotics Research
Towards geometric mapping for semi-autonomous mobile robots
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
Object detection, shape recovery, and 3D modelling by depth-encoded hough voting
Computer Vision and Image Understanding
Efficient 3D object perception and grasp planning for mobile manipulation in domestic environments
Robotics and Autonomous Systems
Real-time plane segmentation using RGB-D cameras
Robot Soccer World Cup XV
Incremental object learning and robust tracking of multiple objects from RGB-D point set data
Journal of Visual Communication and Image Representation
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In this paper we present a framework for 3D geometric shape segmentation for close-range scenes used in mobile manipulation and grasping, out of sensed point cloud data. Our proposed approach proposes a robust geometric mapping pipeline for large input datasets that extracts relevant objects useful for a personal robotic assistant to perform manipulation tasks. The objects are segmented out from partial views and a reconstructed model is computed by fitting geometric primitive classes such as planes, spheres, cylinders, and cones. The geometric shape coefficients are then used to reconstruct missing data. Residual points are resampled and triangulated, to create smooth decoupled surfaces that can be manipulated. The resulted map is represented as a hybrid concept and is comprised of 3D shape coefficients and triangular meshes used for collision avoidance in manipulation routines.