Fabio Bernardini

University of Pisa

Papers

10

Total Citations

327

H-Index

7

About

Fabio Bernardini is a researcher specializing in UHF-RFID localization, robotics, and smart inventory systems, with a particular focus on applying synthetic aperture radar (SAR) techniques to indoor positioning challenges. His most significant contributions lie in developing and refining SAR-based methods for precisely locating UHF-RFID tags using robot-mounted or drone-mounted reader antennas, work that has garnered substantial attention within the sensing and automation communities — his top papers alone have accumulated over 240 citations. Bernardini's landmark contributions include pioneering the use of multiple trajectory SAR localization (109 citations) and integrating particle swarm optimization (PSO) to enable real-time 3D tag positioning (70 citations), dramatically improving both the speed and accuracy of RFID-based localization. His 2021 work on phase unwrapping and hyperbolic intersection further advanced the algorithmic foundations of the field (63 citations). Beyond pure localization, he has extended this research into practical industrial applications through the MONITOR project, developing autonomous robotic inventory systems tailored for warehouses and retail environments in alignment with Industry 4.0 principles. His multi-antenna sensor fusion approach, combining odometry and RFID data, demonstrates a sophisticated systems-level thinking that bridges signal processing, robotics, and logistics. Bernardini's body of work represents a compelling and increasingly relevant contribution to smart automation and intelligent retail infrastructure.

Research Focus

Key Achievements

7
H-Index
10
Papers
327
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Robot-Based Indoor Positioning of UHF-RFID Tags: The SAR Method With Multiple Trajectories
109 citations · 2020
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: University of Pisa

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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