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Registration is an important step when processing three-dimensional (3-D) point clouds. Applications for registration range from object modeling and tracking, to simultaneous localization and mapping (SLAM). This article presents the open-source point cloud library (PCL) and the tools available for point cloud registration. The PCL incorporates methods for the initial alignment of point clouds using...
3D object and object class recognition gained momentum with the arrival of low-cost RGB-D sensors and enables robotics tasks not feasible years ago. Scaling object class recognition to hundreds of classes still requires extensive time and many objects for learning. To overcome the training issue, we introduce a methodology for learning 3D descriptors from synthetic CAD-models and classification of...
In this paper, we present a novel multi-resolution approach to efficiently mapping 3D environments. Our representation models the environment as a hierarchy of probabilistic 3D maps, in which each submap is updated and transformed individually. In addition to the formal description of the approach, we present an implementation for tabletop manipulation tasks and an information-driven exploration algorithm...
In this paper, we present a novel multi-resolution approach to efficiently mapping 3D environments. Our representation models the environment as a hierarchy of probabilistic 3D maps, in which each submap is updated and transformed individually. In addition to the formal description of the approach, we present an implementation for tabletop manipulation tasks and an information-driven exploration algorithm...
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