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About

Shu-Ling Cheng is a researcher specializing in human-robot interaction, augmented reality (AR), virtual reality (VR), and intelligent robotic systems, with a particular focus on advancing intuitive interfaces for industrial robot manipulators. Her work addresses a critical challenge in modern automation: bridging the gap between increasingly capable industrial robots and the often cumbersome, non-intuitive control methods traditionally used to operate them. Cheng's most influential contribution, her 2018 paper on 3D AR-based interfaces for industrial robot manipulators (11 citations), pioneered more natural and efficient approaches to robot task teaching — a pressing concern as Industry 4.0 accelerates factory automation. Complementing this, her research on VR-based manipulation systems and AR-driven teaching and training platforms demonstrates a consistent commitment to making robotics deployment more accessible and effective across industrial settings. Beyond manufacturing environments, Cheng has extended her expertise to assistive robotics, developing a comfort-based motion guidance system for a robot walking helper (9 citations), reflecting her broader interest in human-centered robotic design. Collectively, her body of work, accumulating over 37 citations, positions her as a meaningful contributor to the evolving field of intuitive human-robot interfaces and smart automation systems.