This paper presents a novel sensor-fusion method for indoor vehicle tracking. The phase of the signals backscattered by a set of Ultra High Frequency-Radio Frequency Identification (UHF-RFID) reference tags spread in the scenario is combined with the information acquired by on-board low-cost kinematic sensors. The RFID data are acquired by the on-board reader, during the relative motion of the vehicle with respect to the static reference tags, by resembling a synthetic-array approach, with an advantageous reduction of the reference-tag spatial density. In particular, such phase samples are combined with the kinematic data collected by odometers, through a sensor-fusion approach. The method capability is investigated through a numerical analysis that accounts for the main system parameters. Then, the tracking capability is demonstrated through a measurement campaign in a laboratory test set with a UHF-RFID robot prototype equipped with commercial encoders. Experimental results show an average localization error of centimetre order in the estimation of medium-length trajectories by employing only two reference tags in a relatively small area. The proposed method does not need for any calibration procedure and can be implemented by commercial off-the-shelf (COTS) hardware.
Sensor-Fusion and Tracking Method for Indoor Vehicles with Low-Density UHF-RFID Tags
Motroni, Andrea;Buffi, Alice
;Nepa, Paolo;Tellini, Bernardo
2021-01-01
Abstract
This paper presents a novel sensor-fusion method for indoor vehicle tracking. The phase of the signals backscattered by a set of Ultra High Frequency-Radio Frequency Identification (UHF-RFID) reference tags spread in the scenario is combined with the information acquired by on-board low-cost kinematic sensors. The RFID data are acquired by the on-board reader, during the relative motion of the vehicle with respect to the static reference tags, by resembling a synthetic-array approach, with an advantageous reduction of the reference-tag spatial density. In particular, such phase samples are combined with the kinematic data collected by odometers, through a sensor-fusion approach. The method capability is investigated through a numerical analysis that accounts for the main system parameters. Then, the tracking capability is demonstrated through a measurement campaign in a laboratory test set with a UHF-RFID robot prototype equipped with commercial encoders. Experimental results show an average localization error of centimetre order in the estimation of medium-length trajectories by employing only two reference tags in a relatively small area. The proposed method does not need for any calibration procedure and can be implemented by commercial off-the-shelf (COTS) hardware.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
