Yuliang Xiao
Papers
1
Total Citations
3
H-Index
1
About
Yuliang Xiao is a researcher advancing the frontiers of intelligent manufacturing and human-robot interaction. His work focuses on integrating computer vision, machine learning, and voice recognition technologies to create safer, more intuitive industrial systems. Xiao’s most cited paper, “Emergency Stop System of Computer Vision Workstation Based on GMM-HMM and LSTM” (2023), demonstrates a novel approach to industrial safety by combining Gaussian Mixture Models, Hidden Markov Models, and Long Short-Term Memory networks for real-time voice command recognition. This system allows operators to halt robotic workstations using natural speech, reducing the need for specialized technical skills and enhancing workplace safety. With 3 citations in a rapidly evolving field, Xiao’s research addresses a critical gap in accessible human-robot communication. His work is particularly notable for its practical application in manufacturing environments, where intuitive control interfaces can significantly lower barriers to automation. By pioneering voice-activated emergency stop mechanisms, Xiao contributes to making industrial robotics more user-friendly and responsive, paving the way for broader adoption of intelligent automation in production settings.
Research Focus
Key Achievements
Top Papers
- 1