Efficient RGB-D data processing for feature-based self-localization of mobile robots
[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee
2016
scientific article
english
- visual odometry
- simultaneous localization and mapping
- tracking
- point features
EN The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degreesof freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This workfocuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a singleRGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previousresults as to the general architecture, the important novel elements introduced here are aimed at improving the precisionand 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 andmapping solution. The proposed solutions are tested on publicly available data sets to ensure that the results are scientificallyverifiable. 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.
63 - 79
CC BY-NC-ND (attribution - noncommercial - no derivatives)
open journal
final published version
public
25
1,42