DocumentCode :
2952169
Title :
Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments
Author :
Inkyu Sa ; Hu He ; Van Huynh ; Corke, Peter
Author_Institution :
CyPhy Lab., Queensland Univ. of Technol., Brisbane, QLD, Australia
fYear :
2013
fDate :
9-12 July 2013
Firstpage :
1355
Lastpage :
1360
Abstract :
In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online4.
Keywords :
autonomous aerial vehicles; height measurement; image sensors; minimisation; navigation; robot vision; source coding; state estimation; GPS-denied environments; controller performance; cost function minimization; drift-free altitude measurement; ground truth data acquisition; microaerial vehicles; monocular vision based autonomous navigation system; motion capture system; scale estimator evaluation; source code; state estimator; tutorial documentation; up-to-scale position estimation; visual sensor; Cameras; Kalman filters; Measurement; Navigation; Sensors; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2013 IEEE/ASME International Conference on
Conference_Location :
Wollongong, NSW
ISSN :
2159-6247
Print_ISBN :
978-1-4673-5319-9
Type :
conf
DOI :
10.1109/AIM.2013.6584283
Filename :
6584283
Link To Document :
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