Fuzzy adaptive particle filter for a positioning beacon system

This paper focuses on the localization problem that is to design and deploy an active beacon system specifically for the target environment. Most problems in the 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 for a positioning beacon system. The 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 active ultrasonic beacon systems. For comparison purposes, we test a conventional adaptive particle filter method and our proposed method. Experimental results show that the proposed method can improve the localization performance.