Machine Vision and Applications

, Volume 27, Issue 4, pp 415–436 | Cite as

Vision-based robot localization based on the efficient matching of planar features

  • Baptiste Charmette
  • Eric Royer
  • Frédéric ChausseEmail author
Original Paper


Real-time accurate localization is a key component of any autonomous mobile robot. Visual localization algorithms usually rely on feature matching between the current view and a map using point descriptors. Many descriptors such as SIFT or SURF are designed to recognize features seen from different viewpoints, but in robotics context, robot movement can be modeled to bring useful information for the matching problem. Here we detail a feature-matching solution using a local 3D model of the features that exploits the motion model of the robot. We compare our method against the SIFT descriptor in a simple matching experiment. The method is then combined with prediction models to achieve autonomous navigation of a mobile robot. Experiments showed that localization remains possible despite severe viewpoint change.


Matching Planar feature Image descriptor Robot localization 



This work was financed by the ANR (French National Research Agency) under the cityVIP project framework.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Baptiste Charmette
    • 1
    • 2
  • Eric Royer
    • 1
    • 2
  • Frédéric Chausse
    • 1
    • 2
    Email author
  1. 1.Institut PascalClermont Université, Université d’AuvergneClermont-FerrandFrance
  2. 2.CNRSUMR 6602, IPAubiereFrance

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