Yeeyeng Liau
Papers
1
Total Citations
12
H-Index
1
About
Yeeyeng Liau is a researcher at the forefront of human-robot collaboration, with a focus on integrating augmented reality (AR) into industrial and manufacturing processes. Their most cited work, "A Framework for Process Model Based Human-Robot Collaboration System Using Augmented Reality" (2018), has garnered 12 citations, establishing a foundational approach for enhancing real-time interaction between human workers and robotic systems. Liau’s major contribution lies in developing a process model framework that leverages AR to visualize and guide collaborative tasks, improving safety, efficiency, and task comprehension in dynamic environments. This work bridges the gap between theoretical automation and practical human-robot teamwork, offering a scalable solution for smart factories. By demonstrating how AR can overlay digital instructions onto physical workspaces, Liau has advanced the field of collaborative robotics, making it more accessible for non-expert users. Their research continues to influence the design of intuitive human-machine interfaces, with potential applications in assembly, maintenance, and training. For students and researchers exploring Industry 4.0, Liau’s work provides a clear, actionable model for integrating cognitive assistance into collaborative systems.
Research Focus
Key Achievements
Top Papers
- 1