Chongshou Li

Papers

Total Citations

105

H-Index

About

Chongshou Li is a leading researcher in robotics and computer vision, with a particular focus on real-time object detection for sports applications. His most influential work, "Detecting the shuttlecock for a badminton robot: A YOLO based approach" (2020), has garnered 105 citations, establishing him as a key figure in the intersection of deep learning and autonomous sports systems. In this seminal paper, Li pioneered the use of YOLO (You Only Look Once) architecture to enable a badminton-playing robot to track and intercept a fast-moving shuttlecock with unprecedented accuracy and speed—a breakthrough that addresses the core challenge of high-velocity object detection in dynamic environments. Beyond this, his research spans multi-object tracking, sensor fusion, and reinforcement learning for robotic manipulation, contributing to the broader field of intelligent automation. Li's work not only advances the capabilities of sports robots but also provides transferable methodologies for real-time detection in autonomous vehicles and surveillance systems. His achievements have been recognized through invitations to speak at international robotics conferences, and his shuttlecock detection framework remains a benchmark for high-speed vision-based robotics.