Paper Info
Title
3D mapping for urban service robots
Abstract
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.
Year
DOI
Venue
2009
10.1109/IROS.2009.5354277
IROS
Keywords
Field
DocType
SLAM (robots),geographic information systems,laser ranging,mobile robots,service robots,solid modelling,3D laser range scan,3D mapping,3D point clouds,SLAM algorithm,delayed-state information,geographic information system,mobile robot platform,service robots,simultaneous localization and mapping,urban settings
Geographic information system,Computer vision,Computer science,Artificial intelligence,Probabilistic logic,Simultaneous localization and mapping,Point cloud,Robot,Robotics,Mobile robot,Iterative closest point
Conference
Citations 
PageRank 
References 
8
0.70
9
Authors
4
Name
Order
Citations
PageRank
Rafael Valencia180.70
Ernesto H. Teniente280.70
Eduard Trulls331811.07
Juan Andrade-Cetto41404251.42