4.0 Article

A UHF-RFID Multi-Antenna Sensor Fusion Enables Item and Robot Localization

Journal

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION
Volume 6, Issue -, Pages 456-466

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JRFID.2022.3166354

Keywords

Robot sensing systems; Robots; Location awareness; Antennas; Trajectory; Mobile robots; Radiofrequency identification; RFID robot; RFID sensor fusion; RFID tag localization; robotic inventory; robot localization

Funding

  1. Italian Ministry of Education and Research (MIUR)
  2. PARTITALIA srl within the project MONITOR (A Cyber Physical System for the Automatic and Real-time Monitoring of Items in Industrial Scenarios and Large Warehouses) [CUP B41B20000330005]

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This paper presents a UHF-RFID robotic system that can be used for inventory and localization of tagged items. The system reconstructs the robot's trajectory using a sensor-fusion method and leverages it to localize target tags through a multi-antenna synthetic-aperture-radar approach. Experimental results demonstrate the feasibility and performance of the system.
This paper describes a UHF-RFID robotic system for tagged-item inventory and localization. A mobile robot is equipped with wheeled rotary encoders and a UHF-RFID reader connected to multiple antennas. At first, the robot reconstructs its trajectory by exploiting a sensor-fusion method combining odometry data with phase data gathered by on-board antennas from an infrastructure of passive reference tags. Then, it leverages its reconstructed trajectory to localize target tags placed at unknown locations through a multi-antenna synthetic-aperture-radar (SAR) approach. A Particle Swarm Optimization is applied to speed up the position estimation. An experimental campaign conducted in an office environment is presented to verify the system features and feasibility. The performance of the proposed method for both tag localization and robot self-localization is compared with respect to the case of trajectories reconstructed only by odometry data or through a commercial Laser Range Finder mounted on the robot. Particularly, the effect of the cumulated drift of the estimated trajectory on the tag localization performance is investigated.

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