Yancheng Cao

Papers

Total Citations

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About

Yancheng Cao is pioneering the field of affective human-robot interaction, with a specific focus on enabling robots to perceive and respond to natural human touch. His core research integrates biomimetic sensing, flexible electronics, and data-driven affective computing to bridge the gap between rigid robotic systems and the nuanced, tactile world of human communication. In his highly cited work, "Touch-and-Heal" (2023, 18 citations), Cao proposed a groundbreaking affective computing system that allows robots to accurately interpret a variety of natural tactile gestures—from a comforting pat to a playful nudge—and respond with appropriate emotional feedback. This work is foundational for creating more empathetic and socially intelligent robots. Extending this vision, his paper "Enable Natural Tactile Interaction for Robot Dog" (2023) demonstrates a practical application by designing and implementing large-format, distributed flexible pressure sensors on a robot dog, enabling it to recognize human touch and react in a lifelike manner. By tackling the challenge of making robotic touch perception both accurate and scalable, Cao’s contributions are directly shaping the future of companion robots, therapeutic aids, and more intuitive human-machine interfaces.