Bixi Yan

Beijing Information Science & Technology University

Papers

Total Citations

H-Index

About

Bixi Yan is a robotics researcher whose work centers on computer vision and autonomous perception for humanoid robots, with a particular focus on enabling real-time object detection and spatial localization in dynamic, competitive environments. Yan’s most cited paper, “Humanoid Soccer Robot Target Detection and Localization” (2023), introduces a monocular visual target localization method that combines You Only Look Once v8 (YOLOv8) with the Perspective-3-Point (P3P) algorithm. This approach allows humanoid soccer robots competing in RoboCup to accurately detect and locate targets—such as the ball and goalposts—using only a single camera, significantly reducing hardware complexity while maintaining high precision. By integrating deep learning with geometric pose estimation, Yan has advanced the state of the art in lightweight, real-time perception for resource-constrained robots. Though early in their career, Yan’s work has already garnered citations from peers in robotics and computer vision, signaling its relevance to the RoboCup community and broader autonomous systems research. This contribution not only improves competition performance but also offers transferable techniques for general monocular 3D localization tasks in robotics.