Localization based on the Hybrid Extended Kalman Filter with a highly accurate odometry model of a mobile robot

Huu Cong Tran, Joong Kim Young, Myo Taeg Lim

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

1 Citation (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, 3600 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 publicationHUT-ICCE 2008 - 2nd International Conference on Communications and Electronics
Pages311-316
Number of pages6
Publication statusPublished - 2008 Sep 17
EventHUT-ICCE 2008 - 2nd International Conference on Communications and Electronics - Hoi an, Viet Nam
Duration: 2008 Jun 42008 Jun 6

Other

OtherHUT-ICCE 2008 - 2nd International Conference on Communications and Electronics
CountryViet Nam
CityHoi an
Period08/6/408/6/6

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Keywords

  • Extended Kalman Filter
  • Localization
  • Mobile robot

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

Cite this

Tran, H. C., Young, J. K., & Lim, M. T. (2008). Localization based on the Hybrid Extended Kalman Filter with a highly accurate odometry model of a mobile robot. In HUT-ICCE 2008 - 2nd International Conference on Communications and Electronics (pp. 311-316). [4578978]