Real-Time Accurate Geo-Localization of a MAV with Omnidirectional Visual Odometry and GPS
Abstract
This paper presents a system for direct geo-localization of a MAV in an unknown environment using visual odometry and precise real time kinematic (RTK) GPS information. Visual odometry is performed with a multi-camera system with four fisheye cameras that cover a wide field of view which leads to better constraints for localization due to long tracks and a better intersection geometry. Visual observations from the acquired image sequences are refined with a high accuracy on selected keyframes by an incremental bundle adjustment using the iSAM2 algorithm. The optional integration of GPS information yields long-time stability and provides a direct geo-referenced solution. Experiments show the high accuracy which is below 3 cm standard deviation in position.
Cite
Text
Schneider and Förstner. "Real-Time Accurate Geo-Localization of a MAV with Omnidirectional Visual Odometry and GPS." European Conference on Computer Vision Workshops, 2014. doi:10.1007/978-3-319-16178-5_18Markdown
[Schneider and Förstner. "Real-Time Accurate Geo-Localization of a MAV with Omnidirectional Visual Odometry and GPS." European Conference on Computer Vision Workshops, 2014.](https://mlanthology.org/eccvw/2014/schneider2014eccvw-realtime/) doi:10.1007/978-3-319-16178-5_18BibTeX
@inproceedings{schneider2014eccvw-realtime,
title = {{Real-Time Accurate Geo-Localization of a MAV with Omnidirectional Visual Odometry and GPS}},
author = {Schneider, Johannes and Förstner, Wolfgang},
booktitle = {European Conference on Computer Vision Workshops},
year = {2014},
pages = {271-282},
doi = {10.1007/978-3-319-16178-5_18},
url = {https://mlanthology.org/eccvw/2014/schneider2014eccvw-realtime/}
}