Abstract
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.
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