Passive RFID Couplets as Wireless Interface for Sensor Applications

RFID tags are renowned for their versatility and low cost. In recent years, applications making use of them are growing in number and maturity level, but still lack in combining both communication and sensing optimal performance. The present work shows how to use a couplet of RFID tags as a general transducer of sensor information, able to transform a variation of the impedance of a load to which it is connected into a remotelyreadable phase variation: in such a way, the tags are effectively turned into a wireless interface for the variable load sensor and are moreover able to provide constant antenna matching and hence stable read range

Range and Bearing Estimation of an UHF-RFID Tag Using the Phase of the Backscattered Signal

The narrow bandwidth of UHF RFID signals does not allow the direct measurement of the range between the reader and the tag. A Multi-Hypothesis Extended Kalman Filter is proposed in this paper to solve this issue, by fusing the phase measurements with the odometry readings of a mobile robot. While estimating the tag-reader distance, the proposed approach provides also an on-line estimation of the bearing of the tag. The knowledge of range and bearing is beneficial in positioning-based applications as in robotics, to develop algorithms for reaching and grasping a tagged object or to localize a robot using tags as anchors, or for solving a Simultaneous Localization and Mapping (SLAM) problem if positions of both tags and robot are unknown. A few steps are usually enough to obtain a univocal effective estimate of these quantities, as long as the robot is moving over a non-straight path. A comprehensive numerical analysis supports and assesses the theory

A Multiple Baseline Approach to Face Multipath

The positioning of tagged objects by means of the phase of the backscattered RFID signal is a challenging problem. Several approaches have been conceived in the years to face the problem of the narrow bandwidth of the RFID signal, which produces a periodic, and hence ambiguous, measurement of the tag-reader distance. One possible strategy is to exploit the movement of either the tag or the reader to collect a set of phase measurements which allow to solve the aforementioned ambiguity: this is, e.g., the approach pursued by SAR (Synthetic Aperture Radar) methods. In this article we propose an alternative approach which elaborates the sequence of phase samples in order to discover additional indicators that allow to improve the effectiveness of synthetic aperture methods. In particular we develop a strategy that permits to identify, among a set of measurements, the ones more strongly affected by the multipath. If a pattern emerges among the measurements without significant multipath (and this occurs if a low to moderate level of multipath characterizes the environment), by exploiting the good subset of measurements, it is possible to achieve an improvement in the positioning estimation. The method has been developed for a straight line trajectory: numerical results are reported in this article to illustrate the approach, while experimental results confirm its effectiveness

A Robotic System for Localization of Passive UHF-RFID Tagged Objects on Shelves

This paper faces the problem of a robot that patrols a warehouse and localizes objects on shelves using RFID technology. A two-step localization system has been developed. First, the robot localizes itself by means of a Kalman-based algorithm that fuses robot odometry with the information coming from the phase of the signals of few reference RFID tags deployed along the shelves. Then, the objects on the shelves are localized using an algorithm that matches the phase of the signals from tagged objects collected along specific paths (suitably devised to decouple the estimation problem of the different tag coordinates) with a parametric electromagnetic model. A numerical analysis has been reported to show that the estimation error in the tag coordinates remains in the order of a few centimeters under several operating conditions of the system (e.g., for different values of the standard deviation of the measurement noise or under several parameter perturbations). Experimental tests in real scenarios assess the effectiveness of the system: the average position estimation error of the objects is about 10 cm in the case of cluttered metallic shelves but decreases up to a few centimeters in the case of stacked cartons