Ruochen Yin

University of Science and Technology of China, Institute of Plasma Physics

Papers

Total Citations

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About

Ruochen Yin is a robotics researcher whose work lies at the intersection of precision automation, sensor-based perception, and deep learning for industrial manipulation. His primary research areas include robotic grasping, autonomous assembly, and vision-guided manipulation, with a particular focus on applications in fusion energy environments. Yin’s major contributions include developing a deformation model for on-line precision control of the CFETR multipurpose overload robot, which has garnered 25 citations and addresses critical challenges in remote handling for nuclear fusion reactors. He has also advanced RGB-D and monocular camera-based robotic grasping systems, enabling reliable pick-and-place operations in fusion applications where uncertainty from deep neural network predictions must be carefully managed. His recent work on learning-by-doing for peg-in-hole assembly demonstrates a novel approach to mastering autonomous assembly without extensive pre-programming. With a growing citation impact and a clear trajectory toward robust, uncertainty-aware robotic systems, Yin is establishing himself as a key contributor to the practical deployment of intelligent robotics in high-stakes industrial settings.