Papers
6
Total Citations
113
H-Index
5
About
Aggelos Bletsas is a leading researcher in the intersection of robotics, radio-frequency identification (RFID), and localization, with a focus on enabling autonomous systems to precisely locate passive RFID tags in real-world environments. His major contributions center on developing robust, phase-based methods for 2D and 3D localization of RFID-tagged items, often deploying ground robots and drones equipped with commercial off-the-shelf RFID readers. Notably, his work integrates simultaneous localization and mapping (SLAM) with RFID phase measurements, transforming complex phase data into linear optimization problems for fast, accurate tag positioning. His most cited papers, including "Robust RFID Localization in Multipath With Phase-Based Particle Filtering and a Mobile Robot" (30 citations) and "Robotic Inventorying and Localization of RFID Tags, Exploiting Phase-Fingerprinting" (28 citations), demonstrate significant impact in warehouse and retail inventory management. Bletsas has also pioneered real-time performance assessment and deep learning architectures for RFID localization, as seen in his 2025 work. His research addresses critical challenges in multipath environments and autonomous navigation, offering scalable, low-cost solutions for inventorying and asset tracking.
Research Focus
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- 6Deep Learning for Robotic RFID-Localization1 citations · 2025