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Recent work has demonstrated the potential of actuators consisting of bulk elastomers with phase‐changing inclusions for generating high forces and large volumetric expansions. Simultaneously, granular assemblies have been shown to enable tunable properties via different packings, dynamic moduli via jamming, and compatibility with various printing methods via suspension in carrier fluids. Herein, granular actuators are introduced, which represent a new class of soft actuators made of discrete grains. The soft grains consist of a hyperelastic shell and multiple solvent cores. Upon heating, the encapsulated solvent cores undergo liquid‐to‐gas phase change, inducing rapid and strong volumetric expansion of the hyperelastic shell up to 700%. The grains can be used independently for micro‐actuation, or in granular agglomerates for meso‐ and macroscale actuation, demonstrating the scalability of the granular actuators. Furthermore, the active grains can be suspended in a carrier resin or solvent to enable printable soft actuators via established granular material processing techniques. By combining the advantages of phase‐change soft actuation and granularity, this work presents the opportunity to realize soft actuators with tunable bulk properties, compatibility with self‐assembly techniques, and on‐demand reconfigurability.

Variable stiffness in elastomers can be achieved through the introduction of low melting point alloy particles, such as Field's metal (FM), enabling on‐demand switchable elasticity and anisotropy in response to thermal stimulus. Because the FM particles are thermally transitioned between solid and liquid phases, it is beneficial for the composite to be electrically conductive so the stiffness may be controlled via direct Joule heating. While FM is highly conductive, spherical particles contribute to a high percolation threshold. In this paper, it is shown that the percolation threshold of FM particulate composites can be reduced with increasing particles aspect ratio. Increasing the aspect ratio of phase‐changing fillers also increases the rigid‐to‐soft modulus ratio of the composite by raising the elastic modulus in the rigid state while preserving the low modulus in the soft state. The results indicate that lower quantities of high aspect ratio FM particles can be used to achieve both electrical conductivity and stiffness‐switching via a single solution and without introducing additional conductive fillers. This technique is applied to enable a highly stretchable, variable stiffness, and electrically conductive composite, which, when patterned around an inflatable actuator, allows for adaptable trajectories via selective softening of the surface materials.

One of the key differentiators between biological and artificial systems is the dynamic plasticity of living tissues, enabling adaptation to different environmental conditions, tasks, or damage by reconfiguring physical structure and behavioral control policies. Lack of dynamic plasticity is a significant limitation for artificial systems that must robustly operate in the natural world. Recently, researchers have begun to leverage insights from regenerating and metamorphosing organisms, designing robots capable of editing their own structure to more efficiently perform tasks under changing demands and creating new algorithms to control these changing anatomies. Here, an overview of the literature related to robots that change shape to enhance and expand their functionality is presented. Related grand challenges, including shape sensing, finding, and changing, which rely on innovations in multifunctional materials, distributed actuation and sensing, and somatic control to enable next‐generation shape changing robots are also discussed.

Numerous animals adapt their stiffness during natural motions to increase efficiency or environmental adaptability. For example, octopuses stiffen their tentacles to increase efficiency during reaching, and several species adjust their leg stiffness to maintain stability when running across varied terrain. Inspired by nature, variable‐stiffness machines can switch between rigid and soft states. However, existing variable‐stiffness systems are usually purpose‐built for a particular application and lack universal adaptability. Here, reconfigurable stiffness‐changing skins that can stretch and fold to create 3D structures or attach to the surface of objects to influence their rigidity are presented. These “jamming skins” employ vacuum‐powered jamming of interleaved, discrete planar elements, enabling 2D stretchability of the skin in its soft state. Stretching allows jamming skins to be reversibly shaped into load‐bearing, functional tools on‐demand. Additionally, they can be attached to host structures with complex curvatures, such as robot arms and portions of the human body, to provide support or create a mold. We also show how multiple skins can work together to modify the workspace of a continuum robot by creating instantaneous joints. Jamming skins thus serve as a reconfigurable approach to creating tools and adapting structural rigidity on‐demand.

Soft robot deformations are typically estimated using strain sensors to infer change from a nominal shape while taking a robot‐specific mechanical model into account. This approach performs poorly during buckling and when material properties change with time, and is untenable for shape‐changing robots that don't have a well‐defined resting (unactuated) shape. Herein, these limitations are overcome using stretchable shape sensing (S3) sheets that fuse orientation measurements to estimate 3D surface contours without making assumptions about the underlying robot geometry or material properties. The S3 sheets can estimate the shape of target objects to an accuracy of ≈3 mm for an 80 mm long sheet. The authors show the S3 sheets estimating their shape while being deformed in 3D space and also attached to the surface of a silicone three‐chamber pneumatic bladder, highlighting the potential for shape‐sensing sheets to be applied, removed, and reapplied to soft robots for shape estimation. Finally, the S3 sheets detecting their own stretch up to 30% strain is demonstrated. The approach introduced herein provides a generalized method for measuring the shape of objects without making strong assumptions about the objects, thus achieving a modular, mechanics model‐free approach to proprioception for wearable electronics and soft robotics.