T. Lemaire, Cyrille Berger, I-K. Jung, S. Lacroix. Vision-based SLAM: stereo and monocular approaches. International Journal on Computer Vision, 74(3):343-364, 2007.
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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
[ Slam ]
T. Lemaire
C. Berger
I-K. Jung
S. Lacroix
@article{LEMAIRE-IJCV-2007,
Author = {Lemaire, T. and Berger, Cyrille and Jung, I-K. and Lacroix, S.},
Title = {Vision-based {SLAM}: stereo and monocular approaches},
Journal = {International Journal on Computer Vision},
Volume = {74},
Number = {3},
Pages = {343--364},
Month = {},
Year = {2007}
}
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