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About

Lutao Yan is a robotics researcher whose work spans exoskeleton control, intelligent sorting, and surgical robotics. His primary research areas include human-robot interaction, impedance control for wearable robots, and shape memory alloy (SMA)-actuated continuum mechanisms. Yan’s most cited work, “Research on Impedance Control of an Upper Limb Exoskeleton Robot and Joint Experiments” (2020, 13 citations), introduces a comprehensive impedance control model for upper-limb exoskeletons, detailing both force-based and position-based methods, and optimizing parameters for human-robot interaction. This contribution is foundational for assistive and rehabilitation robotics. In “Coal and Gangue Recognition Method Based on Local Texture Classification Network for Robot Picking” (2021, 9 citations), Yan applies deep learning to industrial automation, improving robotic sorting accuracy in coal mining—a practical solution with significant environmental and economic impact. His reviews and reliability analyses of SMA-driven continuum robots (2021, 4 citations each) advance surgical robotics by addressing actuation challenges in confined spaces, while his system design for a virtual reality-based teleoperated surgical robot (2021, 2 citations) explores master-slave control for minimally invasive surgery. With a focus on bridging theoretical models and real-world applications, Yan’s work demonstrates impact across healthcare, manufacturing, and assistive technologies.