Silica-based distributed fiber-optic sensor (DFOS) systems have been a powerful tool for sensing strain, pressure, vibration, acceleration, temperature, and humidity in inextensible structures. DFOS systems, however, are incompatible with the large strains associated with soft robotics and stretchable electronics. We develop a sensor composed of parallel assemblies of elastomeric lightguides that incorporate continuum or discrete chromatic patterns. By exploiting a combination of frustrated total internal reflection and absorption, stretchable DFOSs can distinguish and measure the locations, magnitudes, and modes (stretch, bend, or press) of mechanical deformation. We further demonstrate multilocation decoupling and multimodal deformation decoupling through a stretchable DFOS–integrated wireless glove that can reconfigure all types of finger joint movements and external presses simultaneously, with only a single sensor in real time.

Technologies that use stretchable materials are increasingly important, yet we are unable to control how they stretch with much more sophistication than inflating balloons. Nature, however, demonstrates remarkable control of stretchable surfaces; for example, cephalopods can project hierarchical structures from their skin in milliseconds for a wide range of textural camouflage. Inspired by cephalopod muscular morphology, we developed synthetic tissue groupings that allowed programmable transformation of two-dimensional (2D) stretchable surfaces into target 3D shapes. The synthetic tissue groupings consisted of elastomeric membranes embedded with inextensible textile mesh that inflated to within 10% of their target shapes by using a simple fabrication method and modeling approach. These stretchable surfaces transform from flat sheets to 3D textures that imitate natural stone and plant shapes and camouflage into their background environments.

Artificial muscles based on stimuli-responsive polymers usually exhibit mechanical compliance, versatility, and high power-to-weight ratio, showing great promise to potentially replace conventional rigid motors for next-generation soft robots, wearable electronics, and biomedical devices. In particular, thermomechanical liquid crystal elastomers (LCEs) constitute artificial muscle-like actuators that can be remotely triggered for large stroke, fast response, and highly repeatable actuations. Here, we introduce a digital light processing (DLP)–based additive manufacturing approach that automatically shear aligns mesogenic oligomers, layer-by-layer, to achieve high orientational order in the photocrosslinked structures; this ordering yields high specific work capacity (63 J kg−1) and energy density (0.18 MJ m−3). We demonstrate actuators composed of these DLP printed LCEs’ applications in soft robotics, such as reversible grasping, untethered crawling, and weightlifting. Furthermore, we present an LCE self-sensing system that exploits thermally induced optical transition as an intrinsic option toward feedback control.

Soft materials possess several distinctive characteristics, such as controllable deformation, infinite degrees of freedom, and self‐assembly, which make them promising candidates for building soft machines, robots, and haptic interfaces. In this Review, we give an overview of recent advances in these areas, with an emphasis on two specific topics: bio‐inspired design and additive manufacturing. Biology is an abundant source of inspiration for functional materials and systems that mimic the function or mechanism of biological tissues, agents, and behaviors. Additive manufacturing has enabled the fabrication of materials and structures prevalent in biology, thereby leading to more‐capable soft robots and machines. We believe that bio‐inspired design and additive manufacturing have been, and will continue to be, important tools for the design of soft robots.