2A1-O01 Two-filter Form型アンセンテッドスムーザを用いた自己位置推定問題の解法(移動ロボットの自己位置推定と地図構築)

概要

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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.
2011-05-26