Abstract
In order to make mobile robots move autonomously, localization problems have been widely researched. Therefore, several methods, such as an extended Kalman filter (EKF) method that is based on the Kalman filter (KF) and an unscented Kalman filter (UKF) that introduces an unscented transformation, have been proposed up to now. On the other hand, it is well known that smoothers can improve the accuracy of the estimation result of the KF. As one of typical smoothers, there is a two-filter form (TF) smoother. To apply it to nonlinear systems as well as the KF, an unscented TF smoother is being developed right now. In this paper, an unscented TF smoother is applied to a localization problem and the accuracy of position estimations is evaluated through simulations.
