Papers

7

Total Citations

96

H-Index

4

About

Matthias Gareis is a leading researcher in ultra-high frequency radio frequency identification (UHF-RFID) and its integration with mobile robotics for autonomous inventory and localization. His work centers on developing smart warehouse systems where robots equipped with RFID technology can automatically identify, locate, and map products in three dimensions. Gareis’s major contributions include pioneering synthetic aperture radar (SAR) techniques for UHF-RFID, enabling centimeter-precision 3D tag localization using cost-effective passive tags. He has also advanced multiple-input multiple-output (MIMO) architectures and particle filter-based approaches for real-time, high-accuracy localization, as well as hybrid systems that fuse RFID with robot odometry for self-localization. His most cited paper (28 citations) introduces stocktaking robots that create 3D product maps, while another (21 citations) details a novel listener hardware for mobile robot MIMO SAR RFID. Gareis has also explored surface acoustic wave (SAW) RFID for industrial IoT applications, including spatial division multiple access. His work has accumulated over 96 citations, demonstrating significant impact in logistics and automation.

Research Focus

Key Achievements

4
H-Index
7
Papers
96
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Stocktaking Robots, Automatic Inventory, and 3D Product Maps: The Smart Warehouse Enabled by UHF-RFID Synthetic Aperture Localization Techniques
28 citations · 2021
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg, Rohde & Schwarz (Germany)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago