WiFi Localization System Using Fuzzy Rule-Based Classification

  • Authors:
  • José M. Alonso;Manuel Ocaña;Miguel A. Sotelo;Luis M. Bergasa;Luis Magdalena

  • Affiliations:
  • European Centre for Soft Computing, Mieres (Asturias), Spain;Department of Electronics, University of Alcalá (Madrid), Spain;Department of Electronics, University of Alcalá (Madrid), Spain;Department of Electronics, University of Alcalá (Madrid), Spain;European Centre for Soft Computing, Mieres (Asturias), Spain

  • Venue:
  • Computer Aided Systems Theory - EUROCAST 2009
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

The framework of this paper is robot localization inside buildings using WiFi signal strength measure. This localization is usually made up of two phases: training and estimation stages. In the former the WiFi signal strength of all visible Access Points (APs) are collected and stored in a database or Wifi map, while in the latter the signal strengths received from all APs at a certain position are compared with the WiFi map to estimate the robot location. This work proposes the use of Fuzzy Rule-based Classification in order to obtain the robot position during the estimation stage, after a short training stage where only a few significant WiFi measures are needed. As a result, the proposed method is easily adaptable to new environments where triangulation algorithms can not be applied since the AP physical location is unknown. It has been tested in a real environment using our own robotic platform. Experimental results are better than those achieved by other classical methods.