DocumentCode :
2033971
Title :
Development of a SIFT based monocular EKF-SLAM algorithm for a small unmanned aerial vehicle
Author :
Suzuki, Taro ; Amano, Yoshiharu ; Hashizume, Takumi
Author_Institution :
Adv. Res. Inst. for Sci. & Eng., Waseda Univ., Tokyo, Japan
fYear :
2011
fDate :
13-18 Sept. 2011
Firstpage :
1656
Lastpage :
1659
Abstract :
This paper describes a simultaneous localization and mapping (SLAM) algorithm using a monocular camera for a small unmanned aerial vehicle (UAV). A small U AV is attracted the attention for effective means of the collecting aerial information. However, there are few practical applications due to its small payloads for the 3D measurement. We propose extended Kalman filter (EKF) SLAM to increase UAV position and attitude data and to construct 3D terrain maps using a small monocular camera. We propose 3D measurement based on scale-invariant feature transform (SIFT) triangulation features extracted from captured images. Field-experiment results show that our proposal effectively estimates U AV position and attitude of the U AV and construct the 3D terrain map.
Keywords :
Kalman filters; SLAM (robots); aerospace robotics; aircraft; mobile robots; remotely operated vehicles; robot vision; transforms; EKF; SIFT development; UAV; extended Kalman filter; monocular EKF-SLAM algorithm; scale invariant feature transform; simultaneous localization and mapping; small unmanned aerial vehicle; Cameras; Feature extraction; Global Positioning System; Simultaneous localization and mapping; Three dimensional displays; Vehicles; Extended Kalman Filter; SIFT; SLAM; Unmanned Aerial Vehicle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual Conference (SICE), 2011 Proceedings of
Conference_Location :
Tokyo
ISSN :
pending
Print_ISBN :
978-1-4577-0714-8
Type :
conf
Filename :
6060231
Link To Document :
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