Structurally Programmed Textile Metasurfaces for Soft Morphing Robotics and Bionic Mimetic Camouflage

Abstract

Natural soft systems capable of reversible shape morphing are ubiquitous in living organisms, enabling remarkable multifunctionality such as continuous motions, dexterous manipulation, and adaptive camouflage. However, replicating these capabilities in synthetic materials remains challenging, primarily due to sophisticated mechanical control, restrictive design flexibility, and limited robustness and scalability. Here, we propose a structure-driven design framework to encode the knitted shells with spatially localized strain constraints for soft robotic systems and mimetic camouflage morphing solely by controlling stitch geometry. By leveraging experiments and theoretical analysis, we decouple the effects of stitch-level topology and yarn composition on fabric macromechanical behavior and achieve programmable mechanical responses in knitted shells through geometric tuning. This also enables robust control of non-Euclidean shape morphing in soft textile robotics, including multi-mode inflatable deformation, sequential motion under a single stimulus, and predefined flat-to-shape Gaussian transformations for dynamic mimetic camouflage. This geometry-informed design strategy can provide new insights into scalable, low-cost and customized soft textile robotics for multifunctional applications, such as tailored wearable devices, camouflage gear skin, and human–robot interactions that are resistant to environmental disturbances.