Tingbo Liao

Guangdong University of Technology, National University of Singapore

Papers

Total Citations

140

H-Index

About

Tingbo Liao is a robotics researcher whose work bridges computer vision and mechanical design, with a focus on creating intelligent systems for dynamic environments. His primary research areas include robotic perception, object tracking, and under-actuated gripper design. Liao’s most impactful contribution is a YOLO-based approach for detecting shuttlecocks in badminton robots (2020, 105 citations), which significantly advanced real-time object detection in high-speed sports contexts. He further refined this work with a Fourier Transform-based Optical flow method (FTOC) for shuttlecock tracking (2019, 31 citations), demonstrating a systematic approach to enabling autonomous badminton play. More recently, Liao has explored mechanical innovation with an under-actuated robotic gripper inspired by human finger mechanics (2024, 4 citations), addressing the longstanding challenge of versatility and adaptability in robotic grasping. This work, though newer, shows promise for applications requiring delicate yet robust manipulation. Across his publications, Liao’s research is characterized by a practical, problem-driven methodology that moves from perception to physical interaction. His work not only contributes to sports robotics but also offers insights into broader challenges in real-time vision and adaptive grasping, making him a notable figure in applied robotics research.