: Stereo and Monocular Approaches
Lemaire, Thomas Berger, Cyrille Jung, Il-Kyun Lacroix, Simon 2007 (English)In: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 74, no 3, 343-364Article in journal (Refereed) Published
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.
bearing only SLAM, interest point matching, 3D SLAM
National CategoryComputer Vision and Robotics (Autonomous Systems)
Identifiersurn:nbn:se:liu:diva-73417 (URN)10.1007/s11263-007-0042-3 (DOI)000248239400008 (ISI)oai:DiVA.org:liu-73417 (OAI)diva2:472027 (DiVA)