FengTao Han
Papers
1
Total Citations
12
H-Index
1
About
FengTao Han is a robotics researcher whose work focuses on advancing human-robot collaboration and intelligent manufacturing. His primary research areas include nonlinear control systems, impedance control, and adaptive trajectory planning for collaborative robotic applications. Han’s most notable contribution is his 2023 paper, "Nonlinear impedance control with trajectory adaptation for collaborative robotic grinding," which has already garnered 12 citations—a strong early impact indicator for a recent publication. This work addresses a critical challenge in industrial robotics: enabling robots to safely and precisely perform grinding tasks alongside human workers by dynamically adjusting their force and motion in real time. By integrating nonlinear impedance control with trajectory adaptation, Han’s approach improves both safety and efficiency in shared workspaces, making it highly relevant for modern manufacturing environments. His research bridges the gap between theoretical control methods and practical robotic applications, offering solutions that enhance the adaptability of collaborative robots. As a rising scholar in the field, Han’s work is poised to influence the next generation of intelligent robotic systems, particularly in tasks requiring delicate force control and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1