@inproceedings{45e3cf572b874dec9298163c87ed3e54,
title = "Fuzzy adaptive particle filter for localization of a mobile robot",
abstract = "Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of local- . ization 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.",
keywords = "Fuzzy logic, Localization, Mobile robot, Particle filter",
author = "Kim, {Young Joong} and Won, {Chan Hee} and Pak, {Jung Min} and Lim, {Myo Taeg}",
year = "2007",
doi = "10.1007/978-3-540-74829-8_6",
language = "English",
isbn = "9783540748281",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 3",
pages = "41--48",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems",
edition = "PART 3",
note = "11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 ; Conference date: 12-09-2007 Through 14-09-2007",
}