Title
Efficient RGB-D data processing for feature-based self-localization of mobile robots Efficient RGB-D data processing for feature-based self-localization of mobile robots
Author
Faculty/Department
Faculty of Applied Engineering Sciences
Publication type
article
Publication
Subject
Mathematics
Engineering sciences. Technology
Computer. Automation
Source (journal)
International Journal of Applied Mathematics and Computer Science
Volume/pages
26(2016) :1 , p. 63-79
ISSN
1641-876X
ISI
000373529100005
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general architecture, the important novel elements introduced here are aimed at improving the precision and robustness of the motion estimate computed from the matching point features of two RGB-D frames. Moreover, we demonstrate that the visual odometry system can serve as the front-end for a pose-based simultaneous localization and mapping solution. The proposed solutions are tested on publicly available data sets to ensure that the results are scientifically verifiable. The experimental results demonstrate gains due to the improved feature extraction and management mechanisms, whereas the performance of the whole navigation system compares favorably to results known from the literature.
E-info
https://repository.uantwerpen.be/docman/iruaauth/7cd735/131990.pdf
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