Characterization of Temperature and Humidity Dependence in Soft Elastomer Behavior.

Soft robots are predicted to operate well in unstructured environments due to their resilience to impacts, embodied intelligence, and potential ability to adapt to uncertain circumstances. Soft robots are of further interest for space and extraterrestrial missions, owing to their lightweight and compressible construction. Most soft robots in the literature to-date are made of elastomer bodies. However, limited data are available on the material characteristics of commonly used elastomers in extreme environments. In this study, we characterize four commonly used elastomers in the soft robotics literature-EcoFlex 00-30, Dragon Skin 10, Smooth-Sil 950, and Sylgard 184-in a temperature range of -40°C to 80°C and humidity range of 5-95% RH. We perform pull-to-failure, stiffness, and stress-relaxation tests. Furthermore, we perform a case study on soft elastomers used in stretchable capacitive sensors to evaluate the implications of the constituent material behavior on component performance. We find that all elastomers show temperature-dependent behavior, with typical stiffening of the material and a lower strain at failure with increasing temperature. The stress-relaxation response to temperature depends on the type of elastomer. Limited material effects are observed in response to different humidity conditions. The mechanical properties of the capacitive sensors are only dependent on temperature, but the measured capacitance shows changes related to both humidity and temperature changes, indicating that component-specific properties need to be considered in tandem with the mechanical design. This study provides essential insights into elastomer behavior for the design and successful operation of soft robots in varied environmental conditions.

Spikebot: A Multigait Tensegrity Robot with Linearly Extending Struts.

Numerous recent research efforts have leveraged networks of rigid struts and flexible cables, called tensegrity structures, to create highly resilient and packable mobile robots. However, the locomotion of existing tensegrity robots is limited in terms of both speed and number of distinct locomotion modes, restricting the environments that a robot is capable of exploring. In this study, we present a tensegrity robot inspired by the volumetric expansion of Tetraodontidae. The robot, referred to herein as Spikebot, employs pneumatically actuated rigid struts to expand its global structure and produce diverse gaits. Spikebot is composed of linear actuators that dually serve as rigid struts linked by elastic cables for stability. The linearly actuating struts can selectively protrude to initiate thrust- and instability-driven locomotion primitives. Such motion primitives allow Spikebot to reliably locomote, achieving rolling, lifting, and jumping. To highlight Spikebot's potential for robotic exploration, we demonstrate how it achieves multi-dimensional locomotion over varied terrestrial conditions.

Multi-modal deformation and temperature sensing for context-sensitive machines.

Owing to the remarkable properties of the somatosensory system, human skin compactly perceives myriad forms of physical stimuli with high precision. Machines, conversely, are often equipped with sensory suites constituted of dozens of unique sensors, each made for detecting limited stimuli. Emerging high degree-of-freedom human-robot interfaces and soft robot applications are delimited by the lack of simple, cohesive, and information-dense sensing technologies. Stepping toward biological levels of proprioception, we present a sensing technology capable of decoding omnidirectional bending, compression, stretch, binary changes in temperature, and combinations thereof. This multi-modal deformation and temperature sensor harnesses chromaticity and intensity of light as it travels through patterned elastomer doped with functional dyes. Deformations and temperature shifts augment the light chromaticity and intensity, resulting in a one-to-one mapping between stimulus modes that are sequentially combined and the sensor output. We study the working principle of the sensor via a comprehensive opto-thermo-mechanical assay, and find that the information density provided by a single sensing element permits deciphering rich and diverse human-robot and robot-environmental interactions.

Designing the pressure-dependent shear modulus using tessellated granular metamaterials.

Jammed packings of granular materials display complex mechanical response. For example, the ensemble-averaged shear modulus 〈G〉 increases as a power law in pressure p for static packings of soft spherical particles that can rearrange during compression. We seek to design granular materials with shear moduli that can either increase or decrease with pressure without particle rearrangements even in the large-system limit. To do this, we construct tessellated granular metamaterials by joining multiple particle-filled cells together. We focus on cells that contain a small number of bidisperse disks in two dimensions. We first study the mechanical properties of individual disk-filled cells with three types of boundaries: periodic boundary conditions (PBC), fixed-length walls (FXW), and flexible walls (FLW). Hypostatic jammed packings are found for cells with FLW, but not in cells with PBC and FXW, and they are stabilized by quartic modes of the dynamical matrix. The shear modulus of a single cell depends linearly on p. We find that the slope of the shear modulus with pressure λ_{c}<0 for all packings in single cells with PBC where the number of particles per cell N≥6. In contrast, single cells with FXW and FLW can possess λ_{c}>0, as well as λ_{c}<0, for N≤16. We show that we can force the mechanical properties of multicell granular metamaterials to possess those of single cells by constraining the end points of the outer walls and enforcing an affine shear response. These studies demonstrate that tessellated granular metamaterials provide a platform for the design of soft materials with specified mechanical properties.

Programming 3D Curves with Discretely Constrained Cylindrical Inflatables.

Programming inflatable systems to deform to desired 3D shapes opens up multifarious applications in robotics, morphing architecture, and interventional medicine. This work elicits complex deformations by attaching discrete strain limiters to cylindrical hyperelastic inflatables. Using this system, a method is presented to solve the inverse problem of programming myriad 3D centerline curves upon inflation. The method entails two steps: first, a reduced-order model generates a conceptual solution giving coarse indications of strain limiter placement on the undeformed cylindrical inflatable. This low-fidelity solution then seeds a finite element simulation nested within an optimization loop to further tune strain limiter parameters. We leverage this framework to achieve functionality through a priori programmed deformations of cylindrical inflatables, including 3D curve matching, self-tying knotting, and manipulation. The results hold broad significance for the emerging computational design of inflatable systems.

Reprogrammable allosteric metamaterials from disordered networks.

Prior works on disordered mechanical metamaterial networks-consisting of fixed nodes connected by discrete bonds-have shown that auxetic and allosteric responses can be achieved by pruning a specific set of the bonds from an originally random network. However, bond pruning is irreversible and yields a single bulk response. Using material stiffness as a tunable design parameter, we create metamaterial networks where allosteric responses are achieved without bond removal. Such systems are experimentally realized through variable stiffness bonds that can strengthen and weaken on-demand. In a disordered mechanical network with variable stiffness bonds, different subsets of bonds can be strategically softened to achieve different bulk responses, enabling a multiplicity of reprogrammable input/output allosteric responses.

Multi-environment robotic transitions through adaptive morphogenesis.

The current proliferation of mobile robots spans ecological monitoring, warehouse management and extreme environment exploration, to an individual consumer's home1-4. This expanding frontier of applications requires robots to transit multiple environments, a substantial challenge that traditional robot design strategies have not effectively addressed5,6. For example, biomimetic design-copying an animal's morphology, propulsion mechanism and gait-constitutes one approach, but it loses the benefits of engineered materials and mechanisms that can be exploited to surpass animal performance7,8. Other approaches add a unique propulsive mechanism for each environment to the same robot body, which can result in energy-inefficient designs9-11. Overall, predominant robot design strategies favour immutable structures and behaviours, resulting in systems incapable of specializing across environments12,13. Here, to achieve specialized multi-environment locomotion through terrestrial, aquatic and the in-between transition zones, we implemented 'adaptive morphogenesis', a design strategy in which adaptive robot morphology and behaviours are realized through unified structural and actuation systems. Taking inspiration from terrestrial and aquatic turtles, we built a robot that fuses traditional rigid components and soft materials to radically augment the shape of its limbs and shift its gaits for multi-environment locomotion. The interplay of gait, limb shape and the environmental medium revealed vital parameters that govern the robot's cost of transport. The results attest that adaptive morphogenesis is a powerful method to enhance the efficiency of mobile robots encountering unstructured, changing environments.

Are Liquid Metals Bulk Conductors?

Stretchable electronics have potential in wide-reaching applications including wearables, personal health monitoring, and soft robotics. Many recent advances in stretchable electronics leverage liquid metals, particularly eutectic gallium-indium (EGaIn). A variety of EGaIn electromechanical behaviors have been reported, ranging from bulk conductor responses to effectively strain-insensitive responses. However, numerous measurement techniques have been used throughout the literature, making it difficult to directly compare the various proposed formulations. Here, the electromechanical responses of EGaIn found in the literature is reviewed and pure EGaIn is investigated using three electrical resistance measurement techniques: four point probe, two point probe, and Wheatstone bridge. The results indicate substantial differences in measured electromechanical behavior between the three methods, which can largely be accounted for by correcting for a fixed offset corresponding to the resistances of various parts of the measurement circuits. Yet, even accounting for several of these sources of experimental error, the average relative change in resistance of EGaIn is found to be lower than that predicted by the commonly used bulk conductor assumption, referred to as Pouillet's law. Building upon recent theories proposed in the literature, possible explanations for the discrepancies are discussed. Finally, suggestions are provided on experimental design to enable reproducible and interpretable research.

Soft Actuators Made of Discrete Grains.

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.

Tensegrity Robotics.

Numerous recent advances in robotics have been inspired by the biological principle of tensile integrity-or "tensegrity"-to achieve remarkable feats of dexterity and resilience. Tensegrity robots contain compliant networks of rigid struts and soft cables, allowing them to change their shape by adjusting their internal tension. Local rigidity along the struts provides support to carry electronics and scientific payloads, while global compliance enabled by the flexible interconnections of struts and cables allows a tensegrity to distribute impacts and prevent damage. Numerous techniques have been proposed for designing and simulating tensegrity robots, giving rise to a wide range of locomotion modes, including rolling, vibrating, hopping, and crawling. In this study, we review progress in the burgeoning field of tensegrity robotics, highlighting several emerging challenges, including automated design, state sensing, and kinodynamic motion planning.

Reprogrammable soft actuation and shape-shifting via tensile jamming.

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.

Static-state particle fabrication via rapid vitrification of a thixotropic medium.

Functional particles that respond to external stimuli are spurring technological evolution across various disciplines. While large-scale production of functional particles is needed for their use in real-life applications, precise control over particle shapes and directional properties has remained elusive for high-throughput processes. We developed a high-throughput emulsion-based process that exploits rapid vitrification of a thixotropic medium to manufacture diverse functional particles in large quantities. The vitrified medium renders stationary emulsion droplets that preserve their shape and size during solidification, and energetic fields can be applied to build programmed anisotropy into the particles. We showcase mass-production of several functional particles, including low-melting point metallic particles, self-propelling Janus particles, and unidirectionally-magnetized robotic particles, via this static-state particle fabrication process.

Printed and Laser-Activated Liquid Metal-Elastomer Conductors Enabled by Ethanol/PDMS/Liquid Metal Double Emulsions.

Soft electronic systems require stretchable, printable conductors for applications in soft robotics, wearable technologies, and human-machine interfaces. Gallium-based room-temperature liquid metals (LMs) have emerged as promising candidates, and recent liquid metal-embedded elastomers (LMEEs) have demonstrated favorable properties such as stable conductivity during strain, cyclic durability, and patternability. Here, we present an ethanol/polydimethylsiloxane/liquid metal (EtOH/PDMS/LM) double emulsion ink that enables a fast, scalable method to print LM conductors with high conductivity (7.7 × 105 S m-1), small resistance change when strained, and consistent cyclic performance (over 10,000 cycles). EtOH, the carrier solvent, is leveraged for its low viscosity to print the ink onto silicone substrates. PDMS resides at the EtOH/LM interface and cures upon deposition and EtOH evaporation, consequently bonding the LM particles to each other and to the silicone substrate. The printed PDMS-LM composite can be subsequently activated by direct laser writing, forming high-resolution electrically conductive pathways. We demonstrate the utility of the double emulsion ink by creating intricate electrical interconnects for stretchable electronic circuits. This work combines the speed, consistency, and precision of laser-assisted manufacturing with the printability, high conductivity, strain insensitivity, and mechanical robustness of the PDMS-LM composite, unlocking high-yield, high-throughput, and high-density stretchable electronics.

Highly stretchable multilayer electronic circuits using biphasic gallium-indium.

Stretchable electronic circuits are critical for soft robots, wearable technologies and biomedical applications. Development of sophisticated stretchable circuits requires new materials with stable conductivity over large strains, and low-resistance interfaces between soft and conventional (rigid) electronic components. To address this need, we introduce biphasic Ga-In, a printable conductor with high conductivity (2.06 × 106 S m-1), extreme stretchability (>1,000%), negligible resistance change when strained, cyclic stability (consistent performance over 1,500 cycles) and a reliable interface with rigid electronics. We employ a scalable transfer-printing process to create various stretchable circuit board assemblies that maintain their performance when stretched, including a multilayer light-emitting diode display, an amplifier circuit and a signal conditioning board for wearable sensing applications. The compatibility of biphasic Ga-In with scalable manufacturing methods, robust interfaces with off-the-shelf electronic components and electrical/mechanical cyclic stability enable direct conversion of established circuit board assemblies to soft and stretchable forms.

Surface Actuation and Sensing of a Tensegrity Structure Using Robotic Skins.

Tensegrity robots comprising solid rods connected by tensile cables are of interest due to their flexible and robust nature, which potentially makes them suitable for uneven and unpredictable environments where traditional robots often struggle. Much progress has been made toward attaining locomotion with tensegrity robots. However, measuring the shape of a dynamic tensegrity without the use of external hardware remains a challenge. Here we show how robotic skins may be attached around the exterior of a tensegrity structure, to both control and measure its shape from its surface. The robotic skins are planar, skin-like membranes with integrated actuators and sensors, which we use to transform a passive tensegrity structure into an active tensegrity robot that performs tasks such as locomotion. In addition, sensors placed on the ends of the tensegrity rods are used to directly measure orientation relative to the ground. The hardware and algorithms presented herein thus provide a platform for surface-driven actuation and intrinsic state estimation of tensegrity structures, which we hope will enable future tensegrity robots to execute precise closed-loop motions in real-world environments.

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization.

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.

Sustainable manufacturing of sensors onto soft systems using self-coagulating conductive Pickering emulsions.

Compliant sensors based on composite materials are necessary components for geometrically complex systems such as wearable devices or soft robots. Composite materials consisting of polymer matrices and conductive fillers have facilitated the manufacture of compliant sensors due to their potential to be scaled in printing processes. Printing composite materials generally entails the use of solvents, such as toluene or cyclohexane, to dissolve the polymer resin and thin down the material to a printable viscosity. However, such solvents cause swelling and decomposition of most polymer substrates, limiting the utility of the composite materials. Moreover, many such conventional solvents are toxic or otherwise present health hazards. Here, sustainable manufacturing of sensors is reported, which uses an ethanol-based Pickering emulsion that spontaneously coagulates and forms a conductive composite. The Pickering emulsion consists of emulsified polymer precursors stabilized by conductive nanoparticles in an ethanol carrier. Upon evaporation of the ethanol, the precursors are released, which then coalesce amid nanoparticle networks and spontaneously polymerize in contact with the atmospheric moisture. We printed the self-coagulating conductive Pickering emulsion onto a variety of soft polymeric systems, including all-soft actuators and conventional textiles, to sensitize these systems. The resulting compliant sensors exhibit high strain sensitivity with negligible hysteresis, making them suitable for wearable and robotic applications.

Electronic skins and machine learning for intelligent soft robots.

Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft and stretchable materials to robotic systems comes a myriad of challenges for sensor integration, including multimodal sensing capable of stretching, embedment of high-resolution but large-area sensor arrays, and sensor fusion with an increasing volume of data. This Review explores the emerging confluence of e-skins and machine learning, with a focus on how roboticists can combine recent developments from the two fields to build autonomous, deployable soft robots, integrated with capabilities for informative touch and proprioception to stand up to the challenges of real-world environments.

Spinal Helical Actuation Patterns for Locomotion in Soft Robots.

Spinal-driven locomotion was first hypothesized to exist in biological systems in the 1980s. However, only recently has the concept been applied to legged robots. In implementing spinal-driven locomotion in robots to-date, researchers have focused on bending in the spine. In this article, we propose an additional mode of spinal-driven locomotion: axial torsion via helical actuation patterns. To study torsional spinal-driven locomotion, a six-legged robot with unactuated legs is used. This robot is designed to be modular to allow for changes in the physical system, such as material stiffness of the spine and legs, and has actuators that spiral around the central elastomeric spine of the robot. A model is provided to explain torsional spinal-driven locomotion. Three spinal gaits are developed to allow the robot to walk forward, through which we demonstrate that the speed of the robot can be influenced by the stiffness of the spine and legs. We also demonstrate that a single gait can be used to drive the robot forward and turn the robot left and right by adjusting the leg positions or foot friction. The results indicate that the inclusion of helical actuation patterns can assist in movement. The addition of these actuation patterns or active axial torsion to future, more complex robots with active leg control may enhance the energy efficiency of locomotion or enable fast, dynamic maneuvering.