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Machine Vision and Applications

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01.05.2016 | Original Paper

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

verfasst von: Baptiste Charmette, Eric Royer, Frédéric Chausse

Erschienen in: Machine Vision and Applications | Ausgabe 4/2016

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Abstract

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.

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Titel: Vision-based robot localization based on the efficient matching of planar features
verfasst von: Baptiste Charmette
Eric Royer
Frédéric Chausse
Publikationsdatum: 01.05.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Machine Vision and Applications / Ausgabe 4/2016
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI: https://doi.org/10.1007/s00138-016-0759-5

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