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Content Provider | IEEE Xplore Digital Library |
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Author | Zhao Shiyu Dong Xiangxu Cui Jinqiang Zong Yao Ang Lin Feng Peng Kemao Chen, B.M. Lee, T.H. |
Copyright Year | 2013 |
Description | Author affiliation: Temasek Labs., Nat. Univ. of Singapore, Singapore, Singapore (Lin Feng; Peng Kemao) || Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore (Dong Xiangxu; Zong Yao Ang; Chen, B.M.; Lee, T.H.) || Grad. Sch. for Integrative Sci. & Eng., Nat. Univ. of Singapore, Singapore, Singapore (Zhao Shiyu; Cui Jinqiang) |
Abstract | This paper presents a novel vision-aided inertial navigation system for navigating a small-scale unmanned aerial vehicle (UAV) in unmapped and GPS-denied environments. Suppose the UAV is equipped with a low-cost inertial measurement unit (IMU), a downward-looking camera, a barometer and a compass. By fusing the measurements of the four sensors using an extended Kalman filter, we can obtain drift-free estimates of the velocity and attitude of the UAV. In the meantime, the drift of the UAV position can be significantly reduced and the unknown biases in the IMU measurements can be identified online. The vision measurement in our navigation system is a homography matrix, which can provide the velocity and attitude information of the UAV. We show flight experimental results to verify the effectiveness and robustness of the proposed navigation system. |
Starting Page | 5101 |
Ending Page | 5106 |
File Size | 2248304 |
Page Count | 6 |
File Format | |
ISBN | 9789881563835 |
ISSN | 19341768 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-07-26 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | TCCT, CAA |
Subject Keyword | vision-based navigation Cameras Educational institutions homography Sensors Acceleration Compass Extended Kalman filter Global Positioning System |
Content Type | Text |
Resource Type | Article |
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