Philipp Vorst and Andreas Zell

Particle Filter-based Trajectory Estimation with Passive UHF RFID Fingerprints in Unknown Environments

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009),
St. Louis, Missouri, USA, October 11-15, 2009, pp. 395-401


Abstract

In this paper we present a novel approach to estimating the trajectory of a robot by means of inexpensive passive RFID tags and odometry in unknown environments. We show how trajectory estimation, a prerequisite of mapping RFID transponder positions without a reference positioning system, can be achieved using a particle filter. The presented technique is based on a non-parametric model of spatial relationships between RFID measurements. It overcomes the noisy nature of RFID measurements and the absence of distance and bearing information. The accuracy of our method is investigated in a series of experiments with a mobile robot.


Download

[pdf] [bib]


BibTeX

@INPROCEEDINGS{vorst2009iros,
  author    = {Philipp Vorst and Andreas Zell},
  title     = {Particle Filter-based Trajectory Estimation with Passive
               {UHF} {RFID} Fingerprints in Unknown Environments},
  booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent
               Robots and Systems (IROS 2009)},
  year      = {2009},
  pages     = {395--401},
  address   = {St. Louis, Missouri, USA},
  month     = {October 11-15},
  doi       = {10.1109/IROS.2009.5354627},
  ee        = {http://dx.doi.org/10.1109/IROS.2009.5354627},
  url       = {http://www.ra.cs.uni-tuebingen.de/publikationen/2009/vorst2009iros-traj-estimation.pdf}
}