Curb feature based localization of a mobile robot in urban road environments

Hyunsuk Lee, Jooyoung Park, Woo Jin Chung

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

11 Citations (Scopus)

Abstract

Urban road environments that have pavement and curb are characterized as semi-structured road environments. In semi-structured road environments, the curb provides useful information for robot navigation. In this paper, we present a practical localization method for outdoor mobile robots using the curb features in semi-structured road environments. The curb features are especially useful in urban environment, where the GPS failures take place frequently. A curb extraction is conducted on the basis of the Kernel Fisher Discriminant Analysis (KFDA) to minimize false detection. We adopt the Extended Kalman Filter (EKF) to combine the curb information with odometry and Differential Global Positioning System (DGPS). The uncertainty models for the sensors are quantitatively analyzed to provide a practical solution.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2794-2799
Number of pages6
EditionJune
ISBN (Electronic)9781479969234
DOIs
Publication statusPublished - 2015 Jun 29
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: 2015 May 262015 May 30

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
NumberJune
Volume2015-June
ISSN (Print)1050-4729

Other

Other2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Country/TerritoryUnited States
CitySeattle
Period15/5/2615/5/30

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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