Yan Shen
Papers
1
Total Citations
2
H-Index
1
About
Yan Shen is a robotics researcher whose work focuses on computational methods for robotic kinematics and motion planning. Their most notable contribution lies in the development of innovative numerical approaches to solving the inverse kinematic problem for serial robots, a fundamental challenge in robotics that determines how a robotic arm must move its joints to achieve a desired end-effector position. In their 2020 paper, Shen introduced a screw theory-based framework that reformulates the inverse kinematic problem as an optimization problem, incorporating a damping term to improve solution stability and convergence. This approach represents a meaningful advance in making robotic motion calculations more robust and computationally tractable. While still an emerging body of work with 2 citations, this research addresses a widely studied problem that sits at the intersection of mathematical optimization and practical robotic control, with direct applications in industrial automation, surgical robotics, and human-robot interaction. Shen's methodology demonstrates a sophisticated integration of classical mechanics principles with modern numerical techniques, positioning their research as a promising contribution to the ongoing effort to make robotic systems more precise, efficient, and adaptable across complex real-world environments.
Research Focus
Key Achievements
Top Papers
- 1