Sensor-based self-localization for wheeled mobile robots

A. Curran, K. J. Kyriakopolous

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

Abstract

In this paper, we demonstrate a reliable and robust algorithm to localize a mobile robot in a relatively consistent with an a priori map indoors environment. This algorithm uses an Extended Kalman Filter that combines deadreckoning, ultrasonic, and infrared sensor data to estimate current position and orientation. Through a thresholding approach, unexpected obstacles can be detected. Experimental results from implementation on our mobile robot, Nomad-200, are also presented.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Editors Anon
PublisherPubl by IEEE
Pages8-13
Number of pages6
ISBN (Print)0818634529
StatePublished - 1993
EventProceedings of the IEEE International Conference on Robotics and Automation - Atlanta, GA, USA
Duration: May 2 1993May 6 1993

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume1
ISSN (Print)1050-4729

Conference

ConferenceProceedings of the IEEE International Conference on Robotics and Automation
CityAtlanta, GA, USA
Period5/2/935/6/93

ASJC Scopus subject areas

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

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