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Vision-Based SLAM: Stereo and Monocular Approaches
LAAS/CNRS 7, Toulouse, France. (RIS)
LAAS/CNRS 7, Toulouse, France.ORCID iD: 0000-0003-3011-1505
LAAS/CNRS 7, Toulouse, France. (RIS)
LAAS/CNRS 7, Toulouse, France. (RIS)
2007 (English)In: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 74, no 3, 343-364 p.Article in journal (Refereed) Published
Abstract [en]

Building a spatially consistent model is a key functionality to endow a mobile robot with autonomy. Without an initial map or an absolute localization means, it requires to concurrently solve the localization and mapping problems. For this purpose, vision is a powerful sensor, because it provides data from which stable features can be extracted and matched as the robot moves. But it does not directly provide 3D information, which is a difficulty for estimating the geometry of the environment. This article presents two approaches to the SLAM problem using vision: one with stereovision, and one with monocular images. Both approaches rely on a robust interest point matching algorithm that works in very diverse environments. The stereovision based approach is a classic SLAM implementation, whereas the monocular approach introduces a new way to initialize landmarks. Both approaches are analyzed and compared with extensive experimental results, with a rover and a blimp.

Place, publisher, year, edition, pages
Kluwer Academic Publishers, 2007. Vol. 74, no 3, 343-364 p.
Keyword [en]
bearing only SLAM, interest point matching, 3D SLAM
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:liu:diva-73417DOI: 10.1007/s11263-007-0042-3ISI: 000248239400008OAI: diva2:472027
Available from: 2012-01-03 Created: 2012-01-03 Last updated: 2016-09-19Bibliographically approved

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Berger, Cyrille
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