Title :
Iterative filtering based on Kazakov linearization
Author :
Yao Zhiying ; Liu Dong
Author_Institution :
Second Artillery Eng. Coll., Xi´an, China
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;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
