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Efficient RGB-D data processing for feature-based self-localization of mobile robots

Kraft M., Nowicki M., Penne R., Schmidt A., Skrzypczyński P.

International Journal of Applied Mathematics and Computer Science

2016

Vol. 26, no. 1

63--79

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.

Comparative assessment of point feature detectors in the context of robot navigation

Schmidt A., Kraft M., Fularz M., Domagała Z.

Journal of Automation Mobile Robotics and Intelligent Systems

2013

Vol. 7, No. 1

11--20

This paper presents evaluation of various contemporary interest point detector and descriptor pairs in the context of robot navigation. The robustness of the detectors and descriptors is assessed using publicly available datasets: the first gathered from the camera mounted on the industrial robot [17] and the second gathered from the mobile robot [20]. The most efficient detectors and descriptors for the visual robot navigation are selected.