DocumentCode :
3730371
Title :
A GA-fuzzy logic based extended Kalman filter for mobile robot localization
Author :
Haijiang Wang; Wenhong Liu; Fugui Zhang;Simon X. Yang; Lin Zhang
Author_Institution :
College of Electronic Engineering, Chengdu University of Information Technology, Sichuan 610225, China
fYear :
2015
Firstpage :
319
Lastpage :
323
Abstract :
The basic requirement of mobile robot localization is to know the information about its position and direction. The extended Kalman filter is an excellent tool to estimate the robot´s posture in its work environment. Traditional extended Kalman filter uses fixed error covariance matrices Q and R, which does not conform the real situation. In this paper, GA-fuzzy logic controller is developed to adjust the error covariance matrices on-line. To improve the accuracy of fuzzy logic controller, a genetic algorithm is developed to tune the membership functions. The simulation results show that the proposed approach has good performance.
Keywords :
"Kalman filters","Mobile robots","Robot sensing systems","Fuzzy logic","Covariance matrices","Robot kinematics"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
Type :
conf
DOI :
10.1109/FSKD.2015.7381961
Filename :
7381961
Link To Document :
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