Papers

9

Total Citations

150

H-Index

6

About

Xinghu Yu is a pioneering researcher at the intersection of robotics, automation, and biomedical engineering, with a core focus on robotic manipulation across scales—from macro-level teleoperation to micro- and nano-manipulation. His major contributions include developing intelligent control systems that integrate vision, force perception, and augmented reality to enhance robot autonomy and human-robot interaction. Notably, his 2023 work on trajectory tracking of variable centroid objects (60 citations) introduces a novel deep learning network for predicting and tracking nonrigid objects during dynamic throwing and catching, a significant advance over traditional rigid-object approaches. His 2022 study on a teleoperated ultrasound system (42 citations) fuses augmented reality with predictive force feedback to mitigate time delays in remote medical procedures, showcasing his impact on healthcare robotics. Yu’s recent work in robotic micromanipulation for organoid biofabrication (2025, 9 citations) addresses critical challenges in standardized, complex tissue manufacturing, with applications in drug screening and personalized therapy. With over 150 total citations, Yu’s research bridges fundamental physics of manipulation with practical, high-impact applications in manufacturing and biomedicine, establishing him as a leader in adaptive, multi-scale robotic systems.

Research Focus

Key Achievements

6
H-Index
9
Papers
150
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Trajectory Tracking of Variable Centroid Objects Based on Fusion of Vision and Force Perception
60 citations · 2023
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 33
🏛 Institutions: University of Nottingham Ningbo China, Harbin Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago