Paper Info
Title
Making visual SLAM consistent with geo-referenced landmarks.
Abstract
This paper presents a solution to the consistency problem of SLAM algorithms. We propose here to model the drift affecting the estimation process. The divergence is seen as a bias on the vehicle localization. By using such a model, we are able to guarantee the consistency of the localization. We developed a filter taking into account the divergence and allowing to easily integrate any information helping to characterize the current drift. Geo-referenced landmarks are used in order to provide an absolute localization and drastically reduce the impact of the divergence. The filter is designed around an Extended Kalman Filter and is totally separated from the classical SLAM algorithm. Our method can consequently be connected to any existing SLAM process without trouble. A vehicle performing monocular SLAM in real time was used to validate our approach with real data. The results show that the integrity of the filter is preserved during the whole trajectory and that geo-referenced information helps reducing the natural SLAM drift.
Year
DOI
Venue
2013
10.1109/IVS.2013.6629525
Intelligent Vehicles Symposium
Keywords
Field
DocType
Kalman filters,SLAM (robots),mobile robots,robot vision,trajectory control,SLAM algorithm,absolute localization,consistency problem,divergence impact reduction,drift modeling,estimation process,extended Kalman filter,filter design,geo-referenced landmark,localization consistency guarantee,monocular SLAM,natural SLAM drift reduction,trajectory,vehicle localization,visual SLAM
Computer vision,Monocular slam,Extended Kalman filter,Robot vision,Computer science,Kalman filter,Artificial intelligence,Trajectory control,Simultaneous localization and mapping,Trajectory,Mobile robot
Conference
ISSN
Citations 
PageRank 
1931-0587
1
0.36
References 
Authors
0
3
Name
Order
Citations
PageRank
Guillaume Bresson1205.83
Romuald Aufrère27111.46
Roland Chapuis329942.01