Kang Chen
Papers
1
Total Citations
47
H-Index
1
About
Kang Chen is a robotics researcher whose work centers on the dynamics and control of robotic manipulator systems. His most recognized contribution is a 2019 study introducing a sophisticated dynamic modeling framework for 6-DOF robot manipulators, a class of articulated robotic arms widely used in industrial automation and precision manufacturing. In this work, Chen developed an innovative approach by integrating a centrosymmetric static friction model with a whale genetic optimization algorithm — a hybrid computational technique that combines bio-inspired metaheuristic search strategies to achieve more accurate and efficient parameter identification. This contribution addresses one of the persistent challenges in robotics: accurately capturing complex frictional behavior at joints, which is critical for high-precision motion control. The paper has accumulated 47 citations, reflecting meaningful engagement from the robotics and control engineering communities. Chen's research sits at the intersection of mechanical modeling, computational intelligence, and control theory, contributing practical tools that enhance the performance and reliability of robotic systems. His work is particularly relevant to researchers and engineers working on robot calibration, trajectory planning, and advanced motion control applications.
Research Focus
Key Achievements
Top Papers
- 1