Cheng-Kai Yao
Papers
2
Total Citations
11
H-Index
2
About
Cheng-Kai Yao investigates the intersection of human-robot interaction and intelligent robotic systems, focusing on how robots perceive and are perceived by humans. His work bridges emotional robotics and advanced sensor-based activity detection. In his highly cited 2020 study (9 citations), Yao systematically examined how robot appearances, voice types, and emotional expressions influence human emotion perception accuracy and subjective responses—a foundational contribution to designing more socially intuitive robots. More recently, he has pioneered enhanced activity monitoring in mechanical robot dogs using dynamic strain-based FBG sensors integrated with YOLO-v7 deep learning (2025, 2 citations). This work addresses a critical need in modern robotics: using vibration and strain data from mechanical activities to diagnose environmental conditions and improve robot intelligence. By combining sensor physics with state-of-the-art computer vision, Yao demonstrates how mechanical robots can achieve finer-grained environmental awareness. His research has direct implications for search-and-rescue, industrial inspection, and companion robotics. Yao’s dual focus on emotional perception and physical activity detection positions him at the forefront of creating robots that are both emotionally attuned and mechanically perceptive.
Research Focus
Key Achievements
Top Papers
- 1
- 2