In this paper, we propose a new method for the localization of RFID tags, by deploying off-the-shelf RFID equipment on a robotic platform. The constructed robot is capable to perform Simultaneous Localization (of its own position) and Mapping (SLAM) of the environment and then locate the RFID tags around its path. The proposed method is based on properly treating the measured phase of the backscattered signal by each tag at the reader’s antenna, located on top of the robot. More specifically, the measured phase samples are reconstructed, such that the 2π discontinuities are eliminated (phase-unwrapping). This allows for the formation of an optimization problem, which can be solved rapidly by standard methods. The proposed method is experimentally compared against the SAR/imaging methods, which represent the accuracy benchmark in prior-art, deploying off-the-shelf equipment. It is shown that the proposed method solves exactly the same problem as holographic-imaging methods, overcoming the grid-density constraints of the latter. Furthermore, the problem, being calculations-grid-independent, is solved orders of magnitude faster, allowing for the applicability of the method in real-time inventorying and localization. It is also shown that the state-of-the-art SLAM method, which is used for the estimation of the trace of the robot, also suffers from errors, which directly affect the accuracy of the RFID localization method. Deployment of reference RFID tags at known positions, seems to significantly reduce such errors.

In this paper we investigate the performance of phase-based fingerprinting for the localization of RFID-tagged items in warehouses and large retail stores, by deploying ground and aerial RFID-equipped robots. The measured phases of the target RFID tags, collected along a given robot’s trajectory, are compared to the corresponding phase-measurements of reference RFID tags; i.e. tags placed at known locations. The advantage of the method is that it doesn’t need to estimate the robot’s trajectory, since estimation is carried out by comparing phase measurements collected at neighboring time-intervals. This is of paramount importance for an RFID equipped drone, destined to fly indoors, since its weight should be kept as low as possible, in order to constrain its diameter correspondingly small. The phase measurements are initially unwrapped and then fingerprinting is applied. We compare the phase-fingerprinting with RSSI based fingerprinting. Phase-fingerprinting is significantly more accurate, because of the shape of the phase-function, which is typically U-shaped, with its minimum, measured at the point of the trajectory, when the robot-tag distance is minimised. Experimental accuracy of 15cm is typically achieved, depending on the density of the reference tags’ grid.