Yat Ming Pang

Hong Kong Polytechnic University

Papers

3

Total Citations

108

H-Index

2

About

Yat Ming Pang is a leading researcher at the intersection of human-robot interaction, mixed reality, and artificial intelligence. His work focuses on developing intelligent systems that enable safe, intuitive collaboration between humans and robots, particularly in industrial settings. Pang’s most significant contribution is his pioneering approach to mutual-cognitive safe human-robot interaction, which integrates augmented reality (AR) with deep reinforcement learning. This work, cited over 104 times, allows robots to understand and predict human intentions while providing real-time visual feedback through AR, creating a shared cognitive workspace that enhances both safety and efficiency. He has also advanced rapid prototyping methodologies for industrial articulated products, using mixed reality to address complex design challenges involving multi-pose constraints and in-field customization. Pang’s research bridges the gap between theoretical AI and practical engineering, offering scalable solutions for personalized robot arms, articulated hoists, and other adaptive manufacturing systems. His work has been recognized for its potential to transform human-robot collaboration, making him a key figure in the development of next-generation, human-aware robotic systems.

Research Focus

Key Achievements

2
H-Index
3
Papers
108
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
An AR-assisted Deep Reinforcement Learning-based approach towards mutual-cognitive safe human-robot interaction
104 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Hong Kong Polytechnic University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago