Stereo parallel tracking and mapping for robot localization
Taihú Pire, Thomas Fischer, Javier Civera, Pablo De Cristóforis, Julio Jacobo Berlles
Abstract
This paper describes a visual SLAM system based on stereo cameras and focused on real-time localization for mobile robots. To achieve this, it heavily exploits the parallel nature of the SLAM problem, separating the time-constrained pose estimation from less pressing matters such as map building and refinement tasks. On the other hand, the stereo setting allows to reconstruct a metric 3D map for each frame of stereo images, improving the accuracy of the mapping process with respect to monocular SLAM and avoiding the well-known bootstrapping problem. Also, the real scale of the environment is an essential feature for robots which have to interact with their surrounding workspace. A series of experiments, on-line on a robot as well as off-line with public datasets, are performed to validate the accuracy and real-time performance of the developed method.
BibTeX
@inproceedings{iros2015_stereoparalleltr,
title = {Stereo parallel tracking and mapping for robot localization},
author = {Taihú Pire and Thomas Fischer and Javier Civera and Pablo De Cristóforis and Julio Jacobo Berlles},
booktitle = {IROS 2015},
year = {2015}
}