DocumentCode :
550294
Title :
Unscented H filter based simultaneous localization and mapping
Author :
Ni Pengfei ; Li Shurong
Author_Institution :
Coll. of Inf. & Control Eng., China Univ. of Pet., Dongying, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
3942
Lastpage :
3946
Abstract :
Simultaneous localization and mapping (SLAM) is concerned to be the key point to realize the real autonomy of mobile robot. Kalman filter has been used as a popular solution by researchers in many SLAM applications. In order to avoid its shortcomings of assumption for Gaussian noises, this paper introduced unscented H filter into SLAM problem. The proposed method requires no a priori knowledge of the noise statistics and relies only upon that the noise is bounded. Simulation results are presented to illustrate the effectiveness of the proposed method.
Keywords :
Gaussian noise; H control; Kalman filters; SLAM (robots); mobile robots; Gaussian noises; Kalman filter; mobile robot; noise statistics; simultaneous localization and mapping; unscented H filter; Covariance matrix; Filtering algorithms; Kalman filters; Mathematical model; Noise; Simultaneous localization and mapping; H filter; SLAM; Unscented Kalman filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000632
Link To Document :
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