LiU Electronic Press
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Author:
Lemaire, Thomas (LAAS/CNRS 7, Toulouse, France) (RIS)
Berger, Cyrille (LAAS/CNRS 7, Toulouse, France)
Jung, Il-Kyun (LAAS/CNRS 7, Toulouse, France) (RIS)
Lacroix, Simon (LAAS/CNRS 7, Toulouse, France) (RIS)
Title:
Vision-Based SLAM: Stereo and Monocular Approaches
Publication type:
Article in journal (Refereed)
Language:
English
Publisher: Kluwer Academic Publishers
Status:
Published
In:
International Journal of Computer Vision(ISSN 0920-5691)(EISSN 1573-1405)
Volume:
74
Issue:
3
Pages:
343-364
Year of publ.:
2007
URI:
urn:nbn:se:liu:diva-73417
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-73417
ISI:
000248239400008
Subject category:
Computer Vision and Robotics (Autonomous Systems)
Keywords(en) :
bearing only SLAM, interest point matching, 3D SLAM
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.

Available from:
2012-01-03
Created:
2012-01-03
Last updated:
2014-04-23
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