Xuemei Ye
Papers
1
Total Citations
35
H-Index
1
About
Xuemei Ye is a researcher specializing in human-robot interaction, teleoperation, and learning from demonstration. Her work addresses a critical challenge in robotics: reducing the cognitive burden on human operators during complex teleoperation tasks. In her most cited paper, "A robotic shared control teleoperation method based on learning from demonstrations" (2019, 35 citations), Ye proposes an innovative shared control framework that blends human commands with autonomous robot behaviors learned from prior demonstrations. This approach enables more intuitive and efficient control, particularly in dynamic environments. By integrating machine learning with robotic control, Ye's contributions help bridge the gap between full human control and full autonomy, paving the way for safer and more accessible robotic systems. Her research has implications for applications ranging from remote surgery to hazardous environment exploration. With a growing citation record, Xuemei Ye is establishing herself as a thoughtful contributor to the field of shared autonomy and intelligent robotic assistance.
Research Focus
Key Achievements
Top Papers
- 1