2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)
DOI: 10.1109/iros.2004.1389947
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3D modeling of indoor environments by a mobile robot with a laser scanner and panoramic camera

Abstract: Abstract-We present a method to acquire a realistic, visually convincing 3D model of indoor office environments based on a mobile robot that is equipped with a laser range scanner and a panoramic camera. The data of the 2D laser scans are used to solve the SLAM problem and to extract walls. Textures for walls and floor are built from the images of a calibrated panoramic camera. Multiresolution blending is used to hide seams in the generated textures.

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Cited by 95 publications
(67 citation statements)
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“…It is an inherently hard problem because noise in the estimate of the robot pose leads to noise in the estimate of the map and vice-versa. Typical SLAM approaches use laser range sensors to build maps in two and three dimensions (e.g., [8,9,3,5,28]). However, in recent years the interest on using cameras as sensors in SLAM has increased.…”
Section: Introductionmentioning
confidence: 99%
“…It is an inherently hard problem because noise in the estimate of the robot pose leads to noise in the estimate of the map and vice-versa. Typical SLAM approaches use laser range sensors to build maps in two and three dimensions (e.g., [8,9,3,5,28]). However, in recent years the interest on using cameras as sensors in SLAM has increased.…”
Section: Introductionmentioning
confidence: 99%
“…One of the results is that the currently used user input from GPS tracks for updating and editing OpenStreetMap data cannot be applied here unless a ubiquitous indoor tracking system has been developed. Other options for indoor data gathering include photo modeling and laser scanning of individual buildings (Biber et al 2004); but this is work intensive, expensive and not a comprehensive way of solving the data problem. Currently, many indoor data already exists in the form of for example YAH maps, CAD plans, CityGML or IFC models.…”
Section: Indoor Navigation: Product-to-market Implicationsmentioning
confidence: 99%
“…Moreover, non-parametric methods, such as the k-means clustering algorithm [22], are also used for the same purpose. In addition to modeling with laser scanners only, other devices, such as panoramic cameras, are used integrated with laser scanners [23]. Besides the techniques for modeling indoor environments, especially for robot navigation, terrains are modeled using airborne laser scanners for obtaining terrestrial information as in [24] and [25].…”
Section: -D Modeling Techniques Allow Describing Environments Includmentioning
confidence: 99%