DocumentCode
3016891
Title
Geo-referencing for UAV navigation using environmental classification
Author
Lindsten, Fredrik ; Callmer, Jonas ; Ohlsson, Henrik ; Törnqvist, David ; Schön, Thomas B. ; Gustafsson, Fredrik
Author_Institution
Dept. of Electr. Eng., Linkoping Univ., Linköping, Sweden
fYear
2010
fDate
3-7 May 2010
Firstpage
1420
Lastpage
1425
Abstract
A UAV navigation system relying on GPS is vulnerable to signal failure, making a drift free backup system necessary. We introduce a vision based geo-referencing system that uses pre-existing maps to reduce the long term drift. The system classifies an image according to its environmental content and thereafter matches it to an environmentally classified map over the operational area. This map matching provides a measurement of the absolute location of the UAV, that can easily be incorporated into a sensor fusion framework. Experiments show that the geo-referencing system reduces the long term drift in UAV navigation, enhancing the ability of the UAV to navigate accurately over large areas without the use of GPS.
Keywords
Global Positioning System; geophysical image processing; image classification; image matching; path planning; remotely operated vehicles; robot vision; sensor fusion; GPS; UAV navigation; drift free backup system; environmental classification; environmental content; image classification; map matching; pre-existing map; sensor fusion; signal failure; vision based geo-referencing system; Cameras; Coordinate measuring machines; Global Positioning System; Noise measurement; Position measurement; Satellite navigation systems; Sensor fusion; Simultaneous localization and mapping; Table lookup; Unmanned aerial vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation (ICRA), 2010 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1050-4729
Print_ISBN
978-1-4244-5038-1
Electronic_ISBN
1050-4729
Type
conf
DOI
10.1109/ROBOT.2010.5509424
Filename
5509424
Link To Document