%0 Conference Paper %1 schneegans2007rfid-snapshots %A Schneegans, Sebastian %A Vorst, Philipp %A Zell, Andreas %B Proceedings of the 3rd European Conference on Mobile Robots (ECMR 2007) %C Freiburg, Germany %D 2007 %K RFID filter fingerprinting location mobile particle robot self-localization %P 241-246 %T Using RFID Snapshots for Mobile Robot Self-Localization %U http://www.ra.cs.uni-tuebingen.de/publikationen/2007/schneegans07ecmr.pdf %X In recent years, radio frequency identification (RFID) has found its way into the field of mobile robot navigation. On the one hand, the technology promises to contribute solutions to common problems in self-localization and mapping such as the data association problem. On the other hand, questions like how to cope with poor or even missing range and bearing information remain open. In this paper, we present a novel method which tackles these challenges: Inspired by vision-based self-localization approaches, it utilizes RFID snapshots for the estimation of the robot pose. Our experiments show that the new technique enables a robot to successfully localize itself in an indoor environment. The accuracy is comparable to the one of a previous approach using an explicit model of detection probabilities. Our method, however, requires fewer iterations of the underlying particle filter in order to converge to the approximate robot pose.

@inproceedings{schneegans2007rfid-snapshots, abstract = {In recent years, radio frequency identification (RFID) has found its way into the field of mobile robot navigation. On the one hand, the technology promises to contribute solutions to common problems in self-localization and mapping such as the data association problem. On the other hand, questions like how to cope with poor or even missing range and bearing information remain open. In this paper, we present a novel method which tackles these challenges: Inspired by vision-based self-localization approaches, it utilizes RFID snapshots for the estimation of the robot pose. Our experiments show that the new technique enables a robot to successfully localize itself in an indoor environment. The accuracy is comparable to the one of a previous approach using an explicit model of detection probabilities. Our method, however, requires fewer iterations of the underlying particle filter in order to converge to the approximate robot pose.}, added-at = {2010-06-10T13:49:15.000+0200}, address = {Freiburg, Germany}, author = {Schneegans, Sebastian and Vorst, Philipp and Zell, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/25b5903baccfe189c28f12d56e6c0754c/fifo79}, booktitle = {Proceedings of the 3rd European Conference on Mobile Robots (ECMR 2007)}, interhash = {8150d1881e4604a315bd4a2fa8cdc93c}, intrahash = {5b5903baccfe189c28f12d56e6c0754c}, keywords = {RFID filter fingerprinting location mobile particle robot self-localization}, month = {September 19-21}, pages = {241-246}, timestamp = {2010-06-10T13:49:15.000+0200}, title = {Using {RFID} Snapshots for Mobile Robot Self-Localization}, url = {http://www.ra.cs.uni-tuebingen.de/publikationen/2007/schneegans07ecmr.pdf}, year = 2007 }