RFID tag bearing estimation for mobile robot localization

Passive RFID provides an inexpensive and effective support to basic mobile robot navigation tasks. Nonetheless, problems related to interference and reflections of the signal, and missing tag range and bearing information are open. In this paper, we present a novel method to estimate the bearing of a passive tag relative to a mobile robot equipped with RFID reader and antennas. The algorithm relies on fuzzy reasoning to both model the RFID device and estimate the tag bearing. As an application of the approach, we describe a landmark-based method to solve the so-called kidnapped robot problem, using tag bearing information and a single visual landmark. Experimental results are presented, proving the effectiveness of the proposed technique. It is shown that the combination of RFID and vision provides accurate robot pose information comparable to that of laser-based Monte Carlo localization, with the additional advantage of relying on low-cost sensors.