Shu‐Guang Kuai
Papers
1
Total Citations
26
H-Index
1
About
Shu-Guang Kuai is a leading researcher in social robotics and human-robot interaction, with a focus on developing more natural and intuitive behaviors for autonomous systems. Their most-cited work, "Human-behaviour-based social locomotion model improves the humanization of social robots" (2022, 26 citations), introduces a groundbreaking framework that enables robots to navigate social spaces by mimicking human movement patterns—such as respecting personal space, adapting to crowd flow, and signaling intent through motion. This contribution directly addresses a critical gap in robotics: the awkwardness of robot navigation in human environments. By grounding locomotion in empirical studies of human social behavior, Kuai’s model enhances both the perceived naturalness and functional efficiency of robots, paving the way for seamless integration into public spaces like hospitals, airports, and shopping centers. Their work has been recognized for bridging computational modeling with cognitive science, offering a scalable solution for next-generation social robots. Kuai’s research continues to influence fields from autonomous navigation to human-robot trust, with their citation record reflecting growing interest in humanizing technology through behavioral fidelity.
Research Focus
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Top Papers
- 1