About

Guanyu Huang is a robotics researcher whose work sits at the intersection of parallel mechanism design, kinematic calibration, and robot perception. His research focuses primarily on the structural synthesis, modeling, and optimization of parallel and hybrid robotic systems, with a particular emphasis on improving their real-world precision and applicability. Huang's most influential contribution — his 2021 work on kinematic calibration of the 3-PRRU parallel manipulator, which has accumulated 47 citations — established a complete, minimal, and continuous error model that significantly advances positioning accuracy in parallel robots. This work is complemented by his broader investigations into identifiable kinematic parameters, offering a rigorous numerical framework for understanding calibration limits in complex mechanisms. Beyond classical robotics, Huang has expanded into cutting-edge domains including neural radiance fields for panoramic robot perception, human-robot interaction — notably contributing to interdisciplinary discussions on communication failures between humans and robots — and the design of novel planar parallel robots using screw theory. His picking-and-placing hybrid robot research further demonstrates his commitment to practical, performance-driven solutions. Across a relatively focused body of work, Huang has established himself as a versatile contributor bridging theoretical kinematics with emerging technologies in robot perception and interaction.

Research Focus

Key Achievements

3
H-Index
6
Papers
66
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Kinematic calibration of a 3-PRRU parallel manipulator based on the complete, minimal and continuous error model
47 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 41
🏛 Institutions: Zhejiang Lab, University of Sheffield, Harbin Institute of Technology, Wuhu Hit Robot Technology Research Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago