Papers

16

Total Citations

1,459

H-Index

8

About

Yuhao Chen is a distinguished researcher whose work spans adaptive control systems, human-robot interaction (HRI), and intelligent automation for industrial and service environments. His most celebrated contribution, "Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints" (2015), has garnered over 1,257 citations, establishing him as a leading voice in neural network-based robotic control, particularly for multi-input/multi-output systems navigating real-world uncertainties. In recent years, Chen has pivoted toward the practical challenges of human-robot collaboration, examining how robots and humans can work safely and efficiently together across diverse settings. His research addresses disassembly sequence planning for e-waste recycling, human workload and ergonomics in collaborative environments, and socially aware robot navigation — all critical concerns as automation becomes increasingly integrated into warehouses, retail spaces, and remanufacturing facilities. Studies on autonomous mobile robots in smart warehouses and retail environments further demonstrate his commitment to understanding both productivity gains and human safety perceptions. Chen's interdisciplinary approach — blending machine learning, ergonomics, and behavioral analysis — makes his work uniquely impactful for engineers and human factors researchers alike, offering concrete pathways toward safer, more intuitive human-robot collaboration in next-generation workplaces.

Research Focus

Key Achievements

8
H-Index
16
Papers
1,459
Total Citations
91
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
1,257 citations · 2015
📈 Most Prolific Year: 2022 (9 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: University of Electronic Science and Technology of China, University of Florida

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago