Papers
18
Total Citations
445
H-Index
8
About
Yongquan Chen is a robotics researcher whose work spans human–robot interaction, space robotics, medical robotics, and autonomous systems. His most influential contribution lies in advancing hand gesture recognition for robot teleoperation: his 2021 paper on dynamic hand gesture recognition using 3D hand pose estimation has garnered 115 citations, establishing a foundational approach that bridges data-glove methodology with vision-based systems. Building on this, Chen developed efficient RGB-D detection frameworks and dual-hand detection methods that enable dexterous robot arm teleoperation with greater accuracy and speed. Chen's research took on urgent real-world significance during the COVID-19 pandemic, when he led the design of a 9-DOF rigid-flexible coupling robot for oropharyngeal swab sampling, protecting frontline medical staff from viral exposure — work that attracted 65 citations and spawned multiple follow-on publications. His earlier investigation of flexible-base space robots for capturing large spacecraft (73 citations) demonstrates a breadth that extends from terrestrial medical applications to orbital environments. More recently, Chen has contributed to visual-inertial odometry for low-texture environments and transformable pipeline inspection robots, reflecting a sustained commitment to solving complex real-world robotic challenges. Collectively, his publications have accumulated over 400 citations, marking him as a significant voice in applied robotics research.
Research Focus
Key Achievements
Top Papers
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- 6A collaborative robot for COVID-19 oropharyngeal swabbing30 citations · 2021
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