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About

Yunsheng Fan is a robotics and automation researcher whose work spans industrial robot systems, computer vision, autonomous vehicles, and intelligent control. His research focuses on advancing precision automation through the integration of machine vision, deep learning, and robotic manipulation — areas of growing importance in modern manufacturing and autonomous systems. Fan's most notable contribution is his development of a robotic grinding workstation combining machine vision with industrial manipulators, addressing critical challenges in automated surface processing and garnering 16 citations since its 2021 publication. His work on 6DOF object positioning using boundary point cloud features has similarly advanced the field of 3D pose estimation for industrial grasping applications. Beyond factory automation, Fan has demonstrated breadth through his design of a heterogeneous marsupial robotic system pairing unmanned surface and aerial vehicles — a creative contribution to multi-robot cooperation. His more recent research explores sophisticated control strategies, including TD3-integrated fuzzy admittance control for precise robotic assembly in unstructured environments, reflecting a trajectory toward intelligent, adaptive systems. Across his career, Fan's publications have collectively accumulated over 40 citations, marking him as a productive contributor to applied robotics research with clear relevance to the future of intelligent manufacturing and autonomous systems.