Cao Xinxin
Papers
1
Total Citations
4
H-Index
1
About
Cao Xinxin is a rising researcher in the field of robotics and human-machine interaction, with a focused expertise in teleoperation and physiological signal processing. Her most cited work, "Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning" (2024), addresses a critical challenge in precision robotics: the degradation of control accuracy caused by involuntary hand tremors in human operators. By integrating deep learning models, Cao has pioneered methods to predict and filter these tremors in real time, significantly enhancing the stability and precision of teleoperated systems used in delicate tasks such as remote surgery or hazardous environment manipulation. Though early in her career, with 4 citations to date, her contribution is notable for bridging neural network techniques with practical robotic control, offering a scalable solution to a long-standing problem. Her work underscores the importance of adaptive algorithms in achieving seamless human-robot collaboration, positioning her as a promising voice in the next generation of robotics researchers.
Research Focus
Key Achievements
Top Papers
- 1