Self-Localization of Mobile Robot using High Accurate Two-Dimensional Geo-Location System

In this paper, we propose an efficient geo-location system for social safety robot using a single base station, where its location is obtained by direction of arrival (DOA) and time of arrival (TOA) of the radio signal. The proposed system requires two reference signals while the conventional systems generally deploy more than three reference signals. For estimating DOA and TOA information together, we employ a multiple signal classification (MUSIC) algorithm. However, the estimation of DOA and TOA using MUSIC algorithm is a time-consuming process. Therefore, we need to compensate the localization error caused by the time delay according to robot motion. For the accurate self-localization of mobile robot, the Unscented Kalman Filter (UKF) is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.