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

Saifudin Razali, Keigo Watanabe, Shoichi Maeyama, Kiyotaka Izumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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 languageEnglish
Title of host publicationSCIS and ISIS 2010 - Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems
Pages1261-1264
Number of pages4
Publication statusPublished - 2010
EventJoint 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 2010Dec 12 2010

Other

OtherJoint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010
CountryJapan
CityOkayama
Period12/8/1012/12/10

Fingerprint

Taylor series
Linearization
Kalman filters
Nonlinear systems
Dynamical systems
Sampling
Derivatives

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

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

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

SCIS and ISIS 2010 - Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. 2010. p. 1261-1264.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Razali, S, Watanabe, K, Maeyama, S & Izumi, K 2010, An Unscented rauch-tung-striebel smoother for a vehicle localization problem. in SCIS and ISIS 2010 - Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. pp. 1261-1264, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010, Okayama, Japan, 12/8/10.
Razali S, Watanabe K, Maeyama S, Izumi K. An Unscented rauch-tung-striebel smoother for a vehicle localization problem. In SCIS and ISIS 2010 - Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. 2010. p. 1261-1264
Razali, Saifudin ; Watanabe, Keigo ; Maeyama, Shoichi ; Izumi, Kiyotaka. / An Unscented rauch-tung-striebel smoother for a vehicle localization problem. SCIS and ISIS 2010 - Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. 2010. pp. 1261-1264
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