International Journal of Computer Vision

, Volume 74, Issue 3, pp 343–364

Vision-Based SLAM: Stereo and Monocular Approaches

  • Thomas Lemaire
  • Cyrille Berger
  • Il-Kyun Jung
  • Simon Lacroix
Article

DOI: 10.1007/s11263-007-0042-3

Cite this article as:
Lemaire, T., Berger, C., Jung, IK. et al. Int J Comput Vision (2007) 74: 343. doi:10.1007/s11263-007-0042-3

Abstract

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.

Keywords

bearing only SLAM interest point matching 3D SLAM 

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Thomas Lemaire
    • 1
  • Cyrille Berger
    • 1
  • Il-Kyun Jung
    • 1
  • Simon Lacroix
    • 1
  1. 1.LAAS/CNRS 7Toulouse Cedex 4France

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