Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information
This paper investigates the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. The paper proposes a vision-based navigation architecture which combines inertial sensors, visual odometry, and registrati...
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2009-01-01
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Series: | EURASIP Journal on Advances in Signal Processing |
Online Access: | http://dx.doi.org/10.1155/2009/387308 |
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doaj-c3b397acf08a48f18e23a4b8147f73a62020-11-25T00:36:12ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802009-01-01200910.1155/2009/387308Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced InformationGianpaolo ContePatrick DohertyThis paper investigates the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. The paper proposes a vision-based navigation architecture which combines inertial sensors, visual odometry, and registration of the on-board video to a geo-referenced aerial image. The vision-aided navigation system developed is capable of providing high-rate and drift-free state estimation for UAV autonomous navigation without the GPS system. Due to the use of image-to-map registration for absolute position calculation, drift-free position performance depends on the structural characteristics of the terrain. Experimental evaluation of the approach based on offline flight data is provided. In addition the architecture proposed has been implemented on-board an experimental UAV helicopter platform and tested during vision-based autonomous flights. http://dx.doi.org/10.1155/2009/387308 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gianpaolo Conte Patrick Doherty |
spellingShingle |
Gianpaolo Conte Patrick Doherty Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information EURASIP Journal on Advances in Signal Processing |
author_facet |
Gianpaolo Conte Patrick Doherty |
author_sort |
Gianpaolo Conte |
title |
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information |
title_short |
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information |
title_full |
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information |
title_fullStr |
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information |
title_full_unstemmed |
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information |
title_sort |
vision-based unmanned aerial vehicle navigation using geo-referenced information |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2009-01-01 |
description |
This paper investigates the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. The paper proposes a vision-based navigation architecture which combines inertial sensors, visual odometry, and registration of the on-board video to a geo-referenced aerial image. The vision-aided navigation system developed is capable of providing high-rate and drift-free state estimation for UAV autonomous navigation without the GPS system. Due to the use of image-to-map registration for absolute position calculation, drift-free position performance depends on the structural characteristics of the terrain. Experimental evaluation of the approach based on offline flight data is provided. In addition the architecture proposed has been implemented on-board an experimental UAV helicopter platform and tested during vision-based autonomous flights. |
url |
http://dx.doi.org/10.1155/2009/387308 |
work_keys_str_mv |
AT gianpaoloconte visionbasedunmannedaerialvehiclenavigationusinggeoreferencedinformation AT patrickdoherty visionbasedunmannedaerialvehiclenavigationusinggeoreferencedinformation |
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1725306321590288384 |