Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments

Sa, Inkyu, He, Hu, Huynh, Van, & Corke, Peter (2013) Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments. In Proceedings of the 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), IEEE, Wollongong, Australia, pp. 1355-1360.

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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 online.

Impact and interest:

5 citations in Scopus
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5 citations in Web of Science®

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ID Code: 62091
Item Type: Conference Paper
Refereed: No
Additional URLs:
Keywords: Monocular vision, Robotics, Autonomous navigation, GPS-denied environments
DOI: 10.1109/AIM.2013.6584283
ISBN: 9781467353199
ISSN: 2159-6247
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
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Deposited On: 27 Aug 2013 23:30
Last Modified: 29 Aug 2013 00:00

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