Fuzzy adaptive particle filter for localization of a mobile robot

Authors:
Young-Joong Kim;Chan-Hee Won;Jung-Min Pak;Myo-Taeg Lim
Affiliations:
Department of Electrical Engineering, Korea University, Seoul, Korea;Department of Electrical Engineering, Korea University, Seoul, Korea;Department of Electrical Engineering, Korea University, Seoul, Korea;Department of Electrical Engineering, Korea University, Seoul, Korea
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Year:
2007

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Abstract

Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of localization are due to uncertainties in the modeling and sensors. Therefore, various filters are developed to estimate the states in noisy information. Recently, particle filter is issued widely because it can be applied to a nonlinear model and a non-Gaussian noise. In this paper a fuzzy adaptive particle filter is proposed, whose basic idea is to generate samples at the high-likelihood using a fuzzy logic approach. The method brings out the improvement of an accuracy of estimation. In addition, this paper presents the localization method for a mobile robot with ultrasonic beacon systems. For comparison purposes, we test a conventional particle filter method and our proposed method. Experimental results show that the proposed method has better localization performance.