DocumentCode
31246
Title
UKF for Integrated Vision and Inertial Sensors Based on Three-View Geometry
Author
Fang, Qing ; Huang, Sheng Xin
Author_Institution
Mobile Robot Navigation and Vision Based Techniques, National University of Defense Technology, Changsha, China
Volume
13
Issue
7
fYear
2013
fDate
Jul-13
Firstpage
2711
Lastpage
2719
Abstract
An unscented Kalman filter (UKF) is derived for integrating vision with inertial measurements from gyros and accelerometers sensors based on three-view geometry. The main goal of the proposed method is to provide better estimations compared to the implicit extended Kalman filter introduced by Indelman . The UKF uses a selected set of points to more accurately map the probability distribution of the measurement model than the linearization of the extended Kalman filter, leading to faster convergence from inaccurate initial conditions in estimation problems. The proposed method is validated using a statistical study based on simulated navigation and synthetic images data.
Keywords
Unscented Kalman filter (UKF); implicit extended Kalman filter (IEKF); sensors; three-view geometry; vision;
fLanguage
English
Journal_Title
Sensors Journal, IEEE
Publisher
ieee
ISSN
1530-437X
Type
jour
DOI
10.1109/JSEN.2013.2259228
Filename
6506954
Link To Document