are specialized for a single task, and cannot adapt their body to accomplish additional tasks after manufacture. Moreover, biological bodies are often highly regenerative, and able to repair and reconfigure their large-scale architecture in the face of significant damage or radical changes to their components. [3] For example, salamanders regenerate amputated limbs, [4] and fragments cut from arbitrary portions of planaria flatworms can rebuild (and rescale) their bodies to recover a full, correct anatomy. [3] Remarkably, many of these systems are able to retain information, such as learned memories, despite drastic reconfiguration or total replacement of their brains. [5] In these integrated living systems, intelligence, memory, learning, behavior, and body structure are all intertwined and emerge from the multiscale dynamics of the same robust and highly fault-tolerant medium.Evolution did not result in hard-coded body plans purely determined by genetic factors, but rather produced diverse examples of intelligent self-modifying systems which adapt to numerous extragenomic influences. [6] In this way, biology serves as an important proof-of-principle, and design challenge, for artificial intelligence and shape changing robots. Despite having access to this extensive set of model systems, the realization of general-purpose, adaptive robots has remained elusive. Researchers have proposed modular robots that can be attached to each other to expand functionality, [7] passively conforming universal grippers, [8] reconfigurable robotic skins, [9] self-assembling robot swarms, [10] gait-switching mechanisms [11] and controllers, [12,13] and algorithms that quickly re-adapt to multiple distinct tasks. [14] Such approaches succeed at adaptation but operate under the assumption that the robot's body is only reconfigured or reshaped due to external forces, and do not explore the possibility of synthetic machines that actively grow, regenerate, deform, or otherwise change the resting shape of their constituent components.With the introduction of a conformable gripper by Hirose in 1978, [15] followed by continuum robot arms, [16] silicone grippers, [17] and variable stiffness actuators, [18] robots that can adapt to real-world environments by changing their shape are becoming closer to reality. In particular, the idea of passively conforming around objects during grasping has been quite successful. [17,19,20] Soft robots have shown potential in other applications, including human-robot interaction and exploration, as reviewed by Kim et al., [21] Rus et al., [22] and others. [23,24] For a comprehensive review of the role of deformation in singlefunction soft robots, the reader is referred to Wang et al. [25] 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 a...

The emerging generation of robots composed of soft materials strives to match biological motor adaptation skills via shape-shifting. Soft robots often harness volumetric expansion directed by strain limiters to deform in complex ways. Traditionally, strain limiters have been inert materials embedded within a system to prescribe a single deformation. Under changing task demands, a fixed deformation mode limits adaptability. Recent technologies for on-demand reprogrammable deformation of soft bodies, including thermally activated variable stiffness materials and jamming systems, presently suffer from long actuation times or introduce unwanted bending stiffness. We present fibers that switch tensile stiffness via jamming of segmented elastic fibrils. When jammed, tensile stiffness increases more than 20× in less than 0.1 s, but bending stiffness increases only 2×. When adhered to an inflating body, jamming fibers locally limit surface tensile strains, unlocking myriad programmable deformations. The proposed jamming technology is scalable, enabling adaptive behaviors in emerging robotic materials that interact with unstructured environments.

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.

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