Ding Yuan

Papers

Total Citations

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About

Ding Yuan is a leading researcher in computer vision and space robotics, with key contributions to satellite pose estimation and 3D reconstruction. His most cited work, "Satellite Pose Estimation via Single Perspective Circle and Line" (2018, 68 citations), tackles a critical challenge in autonomous space operations: determining a satellite’s position and orientation from a single camera view. By leveraging geometric constraints from circular features like docking rings, Yuan developed a method to resolve dual pose ambiguities and recover roll angle—enabling safer, more reliable robotic capture of non-cooperative satellites. This work has direct implications for on-orbit servicing and debris removal missions. Yuan also advanced stereo matching with his "SVCV: segmentation volume combined with cost volume for stereo matching" (2017, 8 citations), which integrates segmentation cues with cost volumes to improve depth estimation in complex 3D scenes. His research bridges foundational computer vision theory with practical aerospace applications, demonstrating how single-view geometry and stereo algorithms can enhance robotic perception in extreme environments. Yuan’s work is widely cited in both robotics and space engineering communities, reflecting its impact on autonomous navigation and satellite servicing technologies.