Xiaopeng Yu
Papers
2
Total Citations
13
H-Index
2
About
Xiaopeng Yu is a robotics researcher specializing in human-robot interaction, assistive robotics, and skill transfer systems. His work focuses on developing intuitive interfaces that allow robots to learn from and collaborate with humans, particularly in mobile and assistive contexts. Yu’s major contributions include the creation of a muscle teleoperation system for a robotic rollator, which uses bilateral shared control to transfer human muscle stiffness signals for enhanced robotic performance—a novel approach that bridges human physiology and machine control. He has also advanced human-robot skill transfer through multi-sensor fusion and teaching by demonstration, enabling mobile robots to generalize skills learned from human interaction in an intuitive way. While his most-cited papers have garnered modest citation counts (8 and 5 citations respectively), his research addresses critical challenges in making assistive robots more responsive and adaptable. Yu’s work on teleoperation and skill transfer has implications for rehabilitation robotics and human-robot collaboration, offering pathways toward more natural and effective human-robot partnerships. His focus on shared control and sensor fusion represents an important step toward robots that can seamlessly integrate into human environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2