Unscented Kalman Filter based Outdoor Localization of a Mobile Robot

Abstract

This paper proposes a practical method, for evaluating positioning of outdoor mobile robots using Unscented Kalman Filter (UKF). Since the UKF method does not require the linearization process unlike EKF localization, it can minimize effects of errors caused by linearization of non-linear models for position estimation. This method enables relatively high performance position estimation, using only non-inertial sensors such as low-precision GPS and a digital compass. Effectiveness of the UKF localization method was verified through actual experiments and performance of position estimation was compared with that of the existing EKF method. Experimental results revealed the proposed method has better performance than the EKF method, and it is stable regardless of initial error size, and observation period.