Improved global localization of an indoor mobile robot via fuzzy extended information filtering

Authors:
Hung-hsing Lin;Ching-chih Tsai
Affiliations:
Department of electrical engineering, national chung hsing university, 250, kuo-kuang road, taichung 40227, taiwan, r.o.c;Department of electrical engineering, national chung hsing university, 250, kuo-kuang road, taichung 40227, taiwan, r.o.c
Venue:
Robotica
Year:
2008

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Abstract

Global localization of mobile robots has been well studied using the extended Kalman filter (EKF) method. This paper presents a fuzzy extended information filtering (FEIF) approach to improving global localization of an indoor autonomous mobile robot with ultrasonic and laser scanning measurements. A real-time FEIF algorithm is proposed to improve accuracy of static global pose estimation via multiple ultrasonic data. By fusing odometric, ultrasonic, and laser scanning data, a real-time FEIF-based pose tracking algorithm is developed to improve accuracy of the robot's continuous poses. Several experimental results are performed to confirm the efficacy of the proposed methods.