Papers
29
Total Citations
665
H-Index
13
About
Paolo Nepa is a prominent researcher specializing in UHF-RFID localization, synthetic aperture radar (SAR) methods, and autonomous robotics systems for indoor positioning. His work sits at the intersection of wireless sensing, signal processing, and intelligent robotics, with a particular focus on enabling precise, real-time tracking in complex indoor environments such as warehouses and smart factories. Nepa's most influential contributions center on leveraging phase measurements from passive UHF-RFID tags to achieve robust localization, bypassing the noise-sensitivity of traditional signal strength approaches. His 2020 paper on SAR-based robot positioning using multiple trajectories has garnered 109 citations, reflecting its foundational impact on the field. Complementary work introducing particle swarm optimization for real-time 3D tag positioning and sensor-fusion methods for indoor vehicle tracking further demonstrate the breadth and practicality of his research. Across his top ten papers alone, Nepa has accumulated over 534 citations, underscoring his substantial influence on the RFID and indoor localization communities. His more recent work integrates passive RFID with IoT sensing capabilities and multi-antenna fusion, extending applications toward environmental mapping and Industry 4.0 ecosystems. For students and researchers exploring smart logistics, autonomous navigation, or RFID-based sensing, Nepa's body of work offers both rigorous methodological foundations and highly practical innovations.
Research Focus
Key Achievements
Top Papers
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- 6SAR-Based Indoor Localization of UHF-RFID Tags via Mobile Robot60 citations · 2018
- 7A UHF-RFID Multi-Antenna Sensor Fusion Enables Item and Robot Localization38 citations · 2022
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- 9Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †24 citations · 2021
- 10Robot Localisation based on Phase Measures of backscattered UHF-RFID Signals13 citations · 2019