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Adaptive extended Kalman filter (AEKF)-based mobile robot localization using sonar

Published online by Cambridge University Press:  18 April 2001

Qing-hao Meng ,
Yi-cai Sun  and
Zuo-liang Cao
Qing-hao Meng
Affiliation:
Hebei University of Technology, 300130, Tianjin (P.R. China)
Yi-cai Sun
Affiliation:
Hebei University of Technology, 300130, Tianjin (P.R. China)
Zuo-liang Cao
Affiliation:
Tianjin Institute of Technology, 300191, Tianjin (P.R. China)
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Abstract

In this paper, an AEKF algorithm is used to localize a mobile robot equipped with eight Polaroid sonars in an indoor structured environment. The system state equation and sonar measurement models used for locating the mobile robot are set up. The localization process based on the AEKF algorithm is given. Four criteria used to judge the validity of predictive measurements of sonars are presented, which can increase the probability of the matching between predictive measurements and actual measurements. Experiments show that the localization precision based on our methods is greater than that using the conventional EKF algorithm.

Keywords

Mobile robotAdaptive extended Kalman filterLocalizationSonar
Type
Research Article
Information
Robotica , Volume 18 , Issue 5 , September 2000 , pp. 459 - 473
Copyright
© 2000 Cambridge University Press

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