Zelin Zhao
Papers
4
Total Citations
42
H-Index
4
About
Zelin Zhao is a leading researcher in human-robot interaction, with a focus on enabling intuitive, real-time motion imitation between humans and life-size humanoid robots. His work centers on the emerging field of Tri-Co Robots—robots designed for cooperative, cognitive, and compliant interaction. Zhao’s major contributions include developing a human-in-the-loop natural teaching paradigm that leverages scene-motion cross-modal perception, allowing operators to telemanipulate humanoid robots through natural gestures rather than complex programming. He also pioneered a novel motion similarity evaluation method using Trajectory Dynamic Time Warping, which precisely quantifies how accurately a robot imitates human motion despite structural differences. His most cited paper (2022, 21 citations) addresses the fundamental challenge of real-time imitation, while his earlier works (2018-2019, 8-9 citations each) established frameworks for first-person-view teleoperation and real-time data retargeting. Zhao’s research bridges the gap between human dexterity and robotic embodiment, with potential applications in remote surgery, hazardous environment exploration, and assistive robotics. His work is particularly notable for advancing natural teaching methods that make humanoid robots more accessible to non-expert users.
Research Focus
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Top Papers
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