Papers

3

Total Citations

27

H-Index

3

About

Haotian Su is advancing the frontier of human-robot collaboration (HRC) by placing human experience at the center of robotic design. His research uniquely bridges wearable sensing, additive manufacturing, and ergonomic modeling to create more intuitive and comfortable interactions between humans and machines. Su’s most cited work, “3D Printed Electromyography Sensing Systems” (2023, 13 citations), tackles the critical challenge of stable EMG signal detection on complex, flexible human skin surfaces—a breakthrough with direct applications in robotics and biomedical diagnostics. He further explores the human dimension of HRC through “Modeling and Analysis of Human Comfort in Human–Robot Collaboration” (2023, 9 citations) and “Measuring Human Comfort in Human–Robot Collaboration via Wearable Sensing” (2024, 5 citations), where he develops novel frameworks and wearable tools to quantify and improve user comfort—an often-overlooked factor in collaborative manufacturing environments. By integrating 3D-printed sensing systems with comfort metrics, Su is not only enhancing robot efficiency and safety but also ensuring that collaborative robots are genuinely designed for people. His work is shaping a future where technology adapts to human needs, making HRC safer, more comfortable, and more effective.

Research Focus

Key Achievements

3
H-Index
3
Papers
27
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
3D Printed Electromyography Sensing Systems
13 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Simon Fraser University, Clemson University, Society of Automotive Engineers International

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago