Papers

18

Total Citations

531

H-Index

12

About

Travis Deyle is a robotics researcher whose work sits at a compelling intersection of assistive technology, human-robot interaction, and wireless sensing systems. Best known for his contributions to robot-assisted living for older adults and people with motor impairments, Deyle has helped lay the empirical groundwork for practical domestic robotics — including a foundational study identifying household objects that people with ALS most need robots to retrieve (63 citations), and influential investigations into medication management assistance for aging-in-place populations (47 citations). A distinctive thread throughout his research is the creative use of UHF RFID technology as a robotic sensing modality. His development of "RF vision" — generating spatial images from RFID signal strength to enable mobile manipulators to locate and grasp tagged objects — earned 53 citations and represents a genuinely novel perceptual approach. Complementary work on probabilistic tag pose estimation and RFID-guided navigation further established him as a leading voice in RF-augmented robotics (44 citations). Deyle also contributed early work on wireless power surfaces for robot swarms (42 citations) and practical locomotion systems for mobile manipulators. His 2012 robotics trends overview (47 citations) reflects his broader influence as a field communicator, making his profile equally valuable to practitioners and students charting the future of assistive robotics.

Research Focus

Key Achievements

12
H-Index
18
Papers
531
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
A list of household objects for robotic retrieval prioritized by people with ALS
63 citations · 2009
📈 Most Prolific Year: 2009 (6 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Georgia Institute of Technology, Duke University, Xidian University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago