DocumentCode
2108407
Title
Iterative filtering based on Kazakov linearization
Author
Yao Zhiying ; Liu Dong
Author_Institution
Second Artillery Eng. Coll., Xi´an, China
fYear
2010
fDate
29-31 July 2010
Firstpage
1369
Lastpage
1374
Abstract
The research on nonlinear filtering algorithm is an active orientation. In this paper, a novel iterative filtering algorithm based on Kazakov linearization is proposed, and the derivation of the algorithm based the Gauss-Newton method is addressed in detail. This algorithm is applied to computer simulation of the SLAM problem in the robot location field and simulation result has been compared with UKF algorithm. The simulation shows that Kazakov based nonlinear filter perform better than UKF algorithm.
Keywords
Gaussian processes; Newton method; SLAM (robots); nonlinear filters; Gauss-Newton method; Kazakov linearization; SLAM problem; computer simulation; iterative filtering; nonlinear filtering algorithm; robot location field; Electronic mail; Filtering algorithms; Iterative algorithm; Kalman filters; Simultaneous localization and mapping; Filtering; Iteravtive; Kazakov Linearization; Nonlinear;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2010 29th Chinese
Conference_Location
Beijing
Print_ISBN
978-1-4244-6263-6
Type
conf
Filename
5573455
Link To Document