T-S fuzzy model adopted SLAM algorithm with linear programming based data association for mobile robots

Keigo Watanabe, Chandima Dedduwa Pathiranage, Kiyoaka Izumi

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

8 Citations (Scopus)

Abstract

This paper describes a Takagi-Sugeno (T-S) fuzzy model adopted solution to the simultaneous localization and mapping (SLAM) problem with two-sensor data association (TSDA) method. Fuzzy Kalman filtering of the SLAM problem (FKF-SLAM) is used in this paper together with newly proposed data association algorithm. An extended TSDA (ETSDA) method is introduced for the SLAM problem in mobile robot navigation based on an interior point linear programming (LP) approach. Simulation results are given to demonstrate that the ETSDA method has low computational complexity and it is more accurate than the existing single-scan joint probabilistic data association (JPDA) method.

Original languageEnglish
Title of host publicationProceedings - IEEE ISIE 2009, IEEE International Symposium on Industrial Electronics
Pages244-249
Number of pages6
DOIs
Publication statusPublished - Dec 1 2009
EventIEEE International Symposium on Industrial Electronics, IEEE ISIE 2009 - Seoul, Korea, Republic of
Duration: Jul 5 2009Jul 8 2009

Publication series

NameIEEE International Symposium on Industrial Electronics

Other

OtherIEEE International Symposium on Industrial Electronics, IEEE ISIE 2009
CountryKorea, Republic of
CitySeoul
Period7/5/097/8/09

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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    Watanabe, K., Pathiranage, C. D., & Izumi, K. (2009). T-S fuzzy model adopted SLAM algorithm with linear programming based data association for mobile robots. In Proceedings - IEEE ISIE 2009, IEEE International Symposium on Industrial Electronics (pp. 244-249). [5217924] (IEEE International Symposium on Industrial Electronics). https://doi.org/10.1109/ISIE.2009.5217924