Sensor‐based self‐localization for wheeled mobile robots

A. Curran, K. J. Kyriakopoulos

Research output: Contribution to journalArticlepeer-review


In this article, we demonstrate a reliable, robust, and computationally efficient algorithm that uses inexpensive hardware to localize a mobile robot in a rather structured environment that is relatively consistent to an a priori map. Furthermore, the incorporation of thresholding makes possible the localization of the robot even in the presence of objects not depicted in the a priori map. An Extended Kalman Filter is used to combine dead‐reckoning, ultrasonic, and infrared sensor data to estimate current position and orientation. Implementation issues and experimental results from experience with a mobile robot, Nomad 200, are also presented. © 1995 John Wiley & Sons, Inc.

Original languageEnglish (US)
Pages (from-to)163-176
Number of pages14
JournalJournal of Robotic Systems
Issue number3
StatePublished - Mar 1995

ASJC Scopus subject areas

  • Control and Systems Engineering


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