An Unscented rauch-tung-striebel smoother for a vehicle localization problem

Saifudin Razali; Keigo Watanabe; Shoichi Maeyama; Kiyotaka Izumi

An Unscented rauch-tung-striebel smoother for a vehicle localization problem

Saifudin Razali, Keigo Watanabe, Shoichi Maeyama, Kiyotaka Izumi

Research output: Contribution to conference › Paper

Abstract

The unscented Kalman filter (UKF) has become relatively a new technique used in a number of nonlinear estimation problems to overcome the limitation of Taylor series linearization. It uses a deterministic sampling approach known as sigma points to propagate nonlinear systems and has been discussed in many literature. However, a nonlinear smoothing problem has received less attention than the filtering problem. Therefore, in this article we examine an unscented smoother based on Rauch-Tung-Striebel form for discrete-time dynamic systems. This smoother has advantages available in unscented transformation over approximation by Taylor expansion as well as its benefit in derivative free. This smoothing technique has been implemented and evaluated through vehicle localization problem.

Original language	English
Pages	1261-1264
Number of pages	4
Publication status	Published - Dec 1 2010
Event	Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010 - Okayama, Japan Duration: Dec 8 2010 → Dec 12 2010

Other

Other	Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010
Country	Japan
City	Okayama
Period	12/8/10 → 12/12/10

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

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Razali, S., Watanabe, K., Maeyama, S., & Izumi, K. (2010). An Unscented rauch-tung-striebel smoother for a vehicle localization problem. 1261-1264. Paper presented at Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010, Okayama, Japan.

An Unscented rauch-tung-striebel smoother for a vehicle localization problem. / Razali, Saifudin; Watanabe, Keigo; Maeyama, Shoichi; Izumi, Kiyotaka.

2010. 1261-1264 Paper presented at Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010, Okayama, Japan.

Research output: Contribution to conference › Paper

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