Yangguang Liu
Papers
3
Total Citations
28
H-Index
3
About
Yangguang Liu is pioneering the intersection of human-robot interaction (HRI) and deep learning to address critical challenges in cognitive development and public safety. His primary research areas include immersive HRI frameworks, intelligent evacuation planning, and the psychosocial dynamics of human-robot proxemics. Liu’s most notable contribution is an immersive, deep learning-driven HRI game framework designed for children’s concentration training, which tackles the shortage of professional trainers and low engagement in traditional methods—a work that has garnered 12 citations. He further explored the nuanced impacts of humanoid robot proximity on concentration games, revealing how spatial dynamics influence therapeutic outcomes. Beyond cognitive training, Liu developed an intelligent evacuation route planning algorithm based on maximum flow theory, optimizing emergency responses for natural and epidemic disasters like COVID-19, with 8 citations. His research not only advances assistive robotics but also provides scalable solutions for real-world crises. By blending technical rigor with human-centered design, Liu is shaping a future where robots serve as both educators and lifesavers.
Research Focus
Key Achievements
Top Papers
- 1
- 2Intelligent Evacuation Route Planning Algorithm Based on Maximum Flow8 citations · 2022
- 3