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Vision-based topological mapping and localization by means of local invariant features and map refinement

Published online by Cambridge University Press:  09 April 2014

Emilio Garcia-Fidalgo  and
Alberto Ortiz
Emilio Garcia-Fidalgo*
Affiliation:
Department of Mathematics and Computer Science, University of the Balearic Islands, Spain
Alberto Ortiz
Affiliation:
Department of Mathematics and Computer Science, University of the Balearic Islands, Spain
*
*Corresponding author. E-mail: emilio.garcia@uib.es
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Summary

We propose an appearance-based approach for topological visual mapping and localization using local invariant features. To optimize running times, matchings between the current image and previously visited places are determined using an index based on a set of randomized kd-trees. We use a discrete Bayes filter for predicting loop candidates, whose observation model is a novel approach based on an efficient matching scheme between features. In order to avoid redundant information in the resulting maps, we also present a map refinement framework, which takes into account the visual information stored in the map for refining the final topology of the environment. These refined maps save storage space and improve the execution times of localizations tasks. The approach is validated using image sequences from several environments and compared with the state-of-the-art FAB-MAP 2.0 algorithm.

Keywords

Topological mapsLoop closureLocalizationMap refinementVisual SLAM

Information

Type
Articles
Information
Robotica , Volume 33 , Issue 7 , August 2015 , pp. 1446 - 1470
Copyright
Copyright © Cambridge University Press 2014 

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