T. Roppel

Auburn University

Papers

7

Total Citations

200

H-Index

6

About

T. Roppel is a leading researcher in the intersection of robotics, RFID technology, and autonomous navigation, with a focus on solving real-world logistical and industrial challenges. Their most influential work, the 2018 paper "BFVP: A Probabilistic UHF RFID Tag Localization Algorithm," has garnered 109 citations and introduces a Bayesian filter-based algorithm combined with a variable power RFID model to precisely locate passive UHF tags in complex environments like warehouses and retail distribution centers. This contribution is complemented by their pioneering work on mobile robots for retail inventory management (41 citations), where they demonstrated a novel autonomous system capable of performing inventory tasks using RFID. Roppel has also made significant strides in robotic path planning, including an optimization approach for minimizing non-working travel in coverage tasks (23 citations) and a reinforcement learning framework for complete coverage path planning in environments with repeated obstacles (2020). Their earlier work on communication models for collaborative robotics and low-cost wireless ad-hoc network testbeds laid the groundwork for multi-agent systems. Additionally, Roppel has applied robotic navigation to corrosion detection in challenging environments, showcasing the versatility of their algorithms. With a career spanning foundational theory to applied systems, Roppel’s research continues to shape how robots interact with and navigate complex, real-world spaces.

Research Focus

Key Achievements

6
H-Index
7
Papers
200
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
BFVP: A Probabilistic UHF RFID Tag Localization Algorithm Using Bayesian Filter and a Variable Power RFID Model
109 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Auburn University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago