An unscented Rauch-Tung-Striebel smoother for SLAM problem

Saifudin Razali, Keigo Watanabe, Shoichi Maeyama, Kiyotaka Izumi

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

1 Citation (Scopus)


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 un-scented 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 Simultaneous Localization and Mapping, SLAM problem.

Original languageEnglish
Title of host publicationSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
PublisherSociety of Instrument and Control Engineers (SICE)
Number of pages5
ISBN (Print)9784907764395
Publication statusPublished - Jan 1 2011
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: Sept 13 2011Sept 18 2011

Publication series

NameProceedings of the SICE Annual Conference


Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011


  • SLAM
  • Unscented transformation
  • nonlinear smoother

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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