Huiying Cai

Zhejiang University, Chinese Academy of Sciences

Papers

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About

Huiying Cai is a researcher whose work bridges the frontiers of robotics, structural mechanics, and intelligent manufacturing. Her primary research areas include tensegrity systems—lightweight, compliant structures composed of tension and compression elements—and advanced heuristic algorithms for industrial automation. In her most-cited paper, "A General Model for Both Shape Control and Locomotion Control of Tensegrity Systems" (2020, 12 citations), Cai proposed a pioneering mathematical framework that unifies shape and locomotion control for these adaptable structures. By integrating a genetic algorithm with the dynamic relaxation method, she enabled tensegrities to function both as configurable architectures and as locomotive robots, opening new possibilities for deployable space structures and soft robotics. Her earlier work, "Heuristic hybrid genetic algorithm based shape matching approach for the pose detection of backlight units in LCD module assembly" (2016, 4 citations), demonstrates her expertise in applying optimization techniques to solve real-world manufacturing challenges, specifically in precision pose detection for electronics assembly. Through these contributions, Cai has established herself as an innovator at the intersection of bio-inspired design and computational engineering, with her tensegrity model serving as a foundational reference for researchers exploring adaptive, multifunctional robotic systems.