Hybrid Extended Kalman Filter-based localization with a highly accurate odometry model of a mobile robot

Tran Him Cong, Young Joong Kim, Myo Taeg Lim

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

13 Citations (Scopus)

Abstract

This paper describes an improving method for solving localization problems with a highly accurate model of a mobile robot either in an uncertainly large-scale environment. Firstly, we motivate our approach by analyzing intensively the dead-reckoning model for the tricycle robot type. Secondly, we propose the localization algorithm based on a Hybrid Extended Kalman Filter using artificial beacons. In this paper, 360° sensor scan is used for each observation and the odometry data is updated to estimate the robot position. Then a comparison between the real and the estimated location of beacons and analyzing of the filter's performance are taken. The simulation results show that the proposed algorithm can lead the robot to robustly navigate in uncertain environments.

Original languageEnglish
Title of host publication2008 International Conference on Control, Automation and Systems, ICCAS 2008
Pages738-743
Number of pages6
DOIs
Publication statusPublished - 2008
Event2008 International Conference on Control, Automation and Systems, ICCAS 2008 - Seoul, Korea, Republic of
Duration: 2008 Oct 142008 Oct 17

Publication series

Name2008 International Conference on Control, Automation and Systems, ICCAS 2008

Other

Other2008 International Conference on Control, Automation and Systems, ICCAS 2008
CountryKorea, Republic of
CitySeoul
Period08/10/1408/10/17

Keywords

  • Extended Kalman filter
  • Localization
  • Mobile robot

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Cong, T. H., Kim, Y. J., & Lim, M. T. (2008). Hybrid Extended Kalman Filter-based localization with a highly accurate odometry model of a mobile robot. In 2008 International Conference on Control, Automation and Systems, ICCAS 2008 (pp. 738-743). [4694596] (2008 International Conference on Control, Automation and Systems, ICCAS 2008). https://doi.org/10.1109/ICCAS.2008.4694596