Papers

7

Total Citations

71

H-Index

5

About

Kang Min is a leading researcher in the field of robotic manipulation and control, with a focus on enhancing the precision, safety, and autonomy of industrial and humanoid robotic systems. His major contributions include developing a model-free calibration method based on improved Kriging interpolation and Kronecker products, which significantly boosts positional accuracy for unopened robotic systems—a breakthrough for high-precision manufacturing. He has also pioneered a novel force control architecture for robotic abrasive belt grinding of complex curved blades, enabling smoother trajectories and superior surface finishing. In trajectory planning, Min introduced a C2 continuous double-spline interpolation method for 6-DOF rotational manipulators, ensuring globally smooth motion. His work on dual-arm adaptive cooperative control for variable loads and active anti-overturning, along with an efficient force/torque sensing method using excitation trajectories, has advanced collaborative robotics. With over 70 citations across his top papers, Min’s research is widely recognized for its practical impact, particularly in robotic calibration and force control. His recent innovations in humanoid upper-body motion optimization and robot-assisted ultrasound calibration without external trackers further demonstrate his versatility, addressing challenges in dynamic environments and medical robotics.

Research Focus

Key Achievements

5
H-Index
7
Papers
71
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
A Robot Positional Error Compensation Method Based on Improved Kriging Interpolation and Kronecker Products
22 citations · 2023
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Harbin Institute of Technology, State Key Laboratory of Robotics and Systems

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago