Self-Localization with RFID snapshots in densely tagged environments

Abstract— In this paper we show that, despite some disadvantageous properties of radio frequency identification (RFID), it is possible to localize a mobile robot quite accurately in environments which are densely tagged. We therefore employ a recently presented probabilistic fingerprinting technique called RFID snapshots. This method interprets short series of RFID measurements as feature vectors and is able to position a mobile robot after a training phase. It requires no explicit sensor model and is capable of exploiting given tag infrastructures, e.g., provided by supermarket shelves containing labeled products.

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Philipp Vorst, Sebastian Schneegans, Bin Yang, Andreas Zell
• Keywords: IROS 2008, Mobile Robot, Probabilistic fingerprinting Technique, RFID Snapshots, Robotics