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
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;
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
DOI :
10.1109/KES.2000.885808
