Yee Yeng Liau
Papers
8
Total Citations
159
H-Index
5
About
Yee Yeng Liau is a leading researcher in human-robot collaboration (HRC), with a focus on transforming manual mold assembly through intelligent automation. Her work addresses critical ergonomic risks in manufacturing—such as repetitive motion and heavy component handling—by designing systems where humans and robots work together safely and efficiently. Liau’s key contributions include developing task allocation algorithms based on task characteristics and agent capability, notably using genetic algorithms to optimize collaboration between multiple cobots. Her 2020 paper on task allocation in HRC for mold assembly has garnered 55 citations, while her 2022 genetic algorithm-based approach has received 51 citations, underscoring the impact of her work. She has also advanced real-time status recognition using pre-trained YOLOv5 for sustainable HRC systems and proposed model-based frameworks with virtual fences to enhance safety in small-batch assembly. More recently, Liau has explored knowledge management and monitoring models to improve adaptability in HRC systems using heterogeneous cobots. Her research not only addresses pressing ergonomic and productivity challenges in low-volume, high-variety production but also provides practical frameworks for deploying collaborative robots in industry. Liau’s work is essential reading for anyone interested in the future of smart manufacturing and human-centered automation.
Research Focus
Key Achievements
Top Papers
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- 7Application Framework of Collaborative Robot to Mold Assembly Processes2 citations · 2022
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