Knitted textile metasurfaces allow soft robots to morph and camouflage on demand

Nature, particularly humans and other animals, has always been among the primary sources of inspiration for roboticists. In fact, most existing robots physically resemble specific animals and/or are engineered to tackle tasks by emulating the actions, movements and behaviors of specific species.

One innate ability of some animals that has so far been seldom replicated in robots is shape morphing and camouflaging. Some living organisms, including some insects, octopuses and chameleons, are known to reversibly change their appearance, form and shape in response to their surroundings, whether to hide from predators, move objects or simply while moving in specific environments.

Researchers at Jiangnan University, Technical University of Dresden, Laurentian University and the Shanghai International Fashion Education Center recently designed new flexible and programmable textile metasurfaces that could be used to develop robots exhibiting similar morphing and camouflaging capabilities. These materials, introduced in a paper published in Advanced Fiber Materials, essentially consist of knitted structures that can be carefully engineered by adapting the geometric arrangement of their underlying interlaced yarn loops.

“In nature, masters of disguise like stick insects and dead-leaf butterflies have perfected shape camouflage over millions of years, while modern camouflage fabrics still rely primarily on static color patterns,” Dr. Fengxin Sun, senior author of the paper, told Tech Xplore.

“This contrast led us to ask: what if camouflage fabrics could dynamically adapt like living organisms, altering both color and texture in real time to match their surroundings? Our goal was to explore how textile structures could be designed to achieve dynamic shape-morphing capabilities, paving the way towards next-generation camouflage technologies that bridge this evolutionary gap.”

A characterizing feature of the textile metasurfaces developed by Dr. Sun and his colleagues is that they can also be programmed by adapting the arrangement of stitches and their geometry, instead of relying only on the composition of the yarn used to create them. By conducting a series of theoretical analyses and real-world experiments, the researchers were able to clearly delineate how the materials they designed changed when changing the arrangement of stitches and the yarn’s composition in specific ways.

“By adjusting the geometric arrangement of fabric stitches, rather than using special yarns, we created the knitted metasurfaces,” explained Sun. “This geometry-driven method allows us to program the fabric’s mechanical behavior using a wide range of yarn types, and offers robust, scalable control that remains stable under varying environmental conditions.”

Initial tests revealed that the newly designed metasurfaces can undergo desirable deformations that are difficult to attain using most of the materials previously used to fabricate soft robots. These include so-called non-Euclidean morphing, Gaussian (curvature-driven) transformations and shape changes prompted by inflation.

“Our study enables precise, programmable fabric deformations in soft textile robotics, from inflatable structures with multiple shape modes, to single-trigger motion sequences, to flat-to-3D camouflage transformations,” said Sun.

“This geometry-informed design opens the door to scalable, low-cost, customizable applications, such as wearable devices, adaptive camouflage skins for defense, wildlife observation, and even adaptive urban clothing for thermoregulation.”

This recent work by Sun and his colleagues could open new, exciting possibilities for the development of a wide range of electronics and robotic systems. In the future, the textile metasurfaces it introduced could be used to create a wide range of programmable systems, including customizable smart gear or adaptable consumer electronics, as well as robots with responsive e-skins that can squeeze in narrow spaces, adapt their shape to better navigate specific environments and hide their presence.

“Our next studies will explore how hierarchical textile structures affect the macromechanics of soft textile robotics, aiming to improve control precision and shape stability,” added Sun. “Alongside this, we plan to design and develop wearable shape-morphing camouflage clothing that could actually be used in real life.”

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