LiU Electronic Press
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Author:
Mejias, Luis (Computer Vision Group, Universidad Polit´ecnica de Madrid, Madrid, Spain)
Campoy, Pascual (Computer Vision Group, Universidad Polit´ecnica de Madrid, Madrid, Spain)
Mondragón, Iván F. (Computer Vision Group, Universidad Polit´ecnica de Madrid, Madrid, Spain)
Doherty, Patrick (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Title:
Stereo visual system for autonomous air vehicle navigation
Department:
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab
Linköping University, The Institute of Technology
Publication type:
Conference paper (Refereed)
Language:
English
In:
6th IFAC Symposium on Intelligent Autonomous Vehicles (2007) Intelligent Autonomous Vehicles, Volume# 6 | Part# 1
Conference:
6th IFAC Symposium on Intelligent Autonomous Vehicles,Toulouse,France, 3-5 September, 2007
Publisher: Elsevier
Series:
IFAC Proceedings series, ISSN 1474-6670
Pages:
203-208
Year of publ.:
2007
URI:
urn:nbn:se:liu:diva-40866
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-40866
ISBN:
978-3-902661-65-4
Local ID:
54434
Subject category:
Computer Science
SVEP category:
Computer science
Abstract(en) :

We present a system to estimate the altitude and motion of an aerial vehicle using a stereo visual system. The system has been initially tested on a ground robot and the novelty lays on its application and robustness validation in an UAV, where vibrations and rapid environmental changes take place. The two main functionalities are height estimation and visual odometry. The system first detects and tracks salient points in the scene. Depth to the plane containing the features is calculated matching features between left and right images then using the disparity principle. Motion is recovered tracking pixels from one frame to the next one finding its visual displacement and resolving camera rotation and translation by a least-square method. We present results from different experimental trials on the two platforms comparing and discussing the results regarding the trajectories calculated by the visual odometry and the onboard helicopter state estimation.

Available from:
2009-10-10
Created:
2009-10-10
Last updated:
2012-09-12
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46 hits