DocumentCode
2656289
Title
A new adaptive Kalman filter applied to visual servoing tasks
Author
Wira, P. ; Urban, J.P.
Author_Institution
TROP Res. Group, Mulhouse Univ., France
Volume
1
fYear
2000
fDate
2000
Firstpage
267
Abstract
A new adaptive Kalman filter is proposed to address the problem of nonlinear systems that cannot be linearized or where the model is unavailable. Using a correlation function of the output vector of a state model system, the transition matrix of the Kalman filter is adjusted to the current situation. This adaptive transition matrix, associated to Kalman gain compensation, produces efficient state estimation. The performance of this predictor has been evaluated on a visual servoing application
Keywords
adaptive Kalman filters; compensation; nonlinear systems; robot vision; state estimation; Kalman gain compensation; adaptive Kalman filter; adaptive transition matrix; correlation function; nonlinear systems; output vector; robot vision; state estimation; state model system; visual servoing tasks; Adaptive filters; Filtering; Image processing; Kalman filters; Nonlinear systems; Robot control; Robot kinematics; Robot vision systems; State estimation; Visual servoing;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
Conference_Location
Brighton
Print_ISBN
0-7803-6400-7
Type
conf
DOI
10.1109/KES.2000.885808
Filename
885808
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