Trabajo presentado al IROS 2009 celebrado en Saint Louis (EE. UU.) del 10 al 15 de octubre. ; We present an approach to the problem of 3D map building in urban settings for service robots, using three-dimensional laser range scans as the main data input. Our system is based on the probabilistic alignment of 3D point clouds employing a delayed-state information-form SLAM algorithm, for which we can add observations of relative robot displacements efficiently. These observations come from the alignment of dense range data point clouds computed with a variant of the iterative closest point algorithm. The datasets were acquired with our custom built 3D range scanner integrated into a mobile robot platform. Our mapping results are compared to a GIS-based CAD model of the experimental site. The results show that our approach to 3D mapping performs with sufficient accuracy to derive traversability maps that allow our service robots navigate and accomplish their assigned tasks on a urban pedestrian area. ; This work was supported by projects: 'Ubiquitous networking robotics in urban settings' (E-00938), 'CONSOLIDER-INGENIO 2010 Multimodal interaction in pattern recognition and computer vision' (V-00069), 'Robotica ubicua para entornos urbanos' (J-01225), 'Percepción y acción ante incertidumbre' (4803), 'Exploración activa para robots móviles urbanos' (4804). This work has been supportedd by scholars ships from the Mexican Council of Science and Technology to R. Valencia and E. Teniente, and from UPC to E. Trulls; by project CSIC-200850 I 107 from CSIC; by projects DPI-2007-614452, DPI-2008-06022, and MIPRCV Consolider-Ingenio 2010 from the Spanish Ministry of Science and Innovation; and by the EU URUS project IST-FP6-STREP-045062. ; Peer Reviewed
3D mapping for urban service robots
2009-01-01
Conference paper
Electronic Resource
English
DDC: | 629 |
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