Chuxuan Chen
Papers
1
Total Citations
3
H-Index
1
About
Chuxuan Chen is a researcher at the intersection of computer vision, robotics, and sports engineering. Their most notable contribution is the development of YOLO-BTM, a novel shuttlecock detection method designed for embedded badminton robots, published in 2022. This work addresses a critical challenge in sports robotics: accurately detecting a fast-moving shuttlecock during flight to enable real-time analysis of athlete movements and prevent training injuries. By adapting the YOLO object detection framework for the unique demands of badminton, Chen has advanced the practical deployment of autonomous training assistants. While the foundational paper has garnered early citations, the work’s significance lies in its applied impact—bridging deep learning with embedded systems to enhance athletic performance analysis. Chen’s research exemplifies how computer vision can transform traditional sports training, offering a scalable solution for precise, injury-aware coaching. This contribution positions them as an emerging voice in the niche but growing field of sports robotics, where real-time detection and motion tracking are key to next-generation training tools.
Research Focus
Key Achievements
Top Papers
- 1