Magnetic soft robotics to manipulate the extracellular matrix in vitro.

The importance of dynamic mechanical control over the cellular microenvironment has long been appreciated. In a recent issue of Device, Raman and colleagues design a clever yet generalizable tool to achieve this, illustrating magnetic stimulation of an engineered extracellular matrix to induce muscle fiber alignment toward programmed functioning.

Movement: How the Brain Communicates with the World.

Voluntary movement is a result of signals transmitted through a communication channel that links the internal world in our minds to the physical world around us. Intention can be considered the desire to effect change on our environment, and this is contained in the signals from the brain, passed through the nervous system to converge on muscles that generate displacements and forces on our surroundings. The resulting changes in the world act to generate sensations that feed back to the nervous system, closing the control loop. This Perspective discusses the experimental and theoretical underpinnings of current models of movement generation and the way they are modulated by external information. Movement systems embody intentionality and prediction, two factors that are propelling a revolution in engineering. Development of movement models that include the complexities of the external world may allow a better understanding of the neuronal populations regulating these processes, as well as the development of solutions for autonomous vehicles and robots, and neural prostheses for those who are motor impaired.

Experiment-free exoskeleton assistance via learning in simulation.

Exoskeletons have enormous potential to improve human locomotive performance1-3. However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws2. Here we show an experiment-free method to learn a versatile control policy in simulation. Our learning-in-simulation framework leverages dynamics-aware musculoskeletal and exoskeleton models and data-driven reinforcement learning to bridge the gap between simulation and reality without human experiments. The learned controller is deployed on a custom hip exoskeleton that automatically generates assistance across different activities with reduced metabolic rates by 24.3%, 13.1% and 15.4% for walking, running and stair climbing, respectively. Our framework may offer a generalizable and scalable strategy for the rapid development and widespread adoption of a variety of assistive robots for both able-bodied and mobility-impaired individuals.

Machine learning reveals the control mechanics of an insect wing hinge.

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs1, but are novel structures that are attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings2. The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the three-dimensional motion of the wings with high-speed cameras. Using machine learning, we created a convolutional neural network3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation incorporating our hinge model generates flight manoeuvres that are remarkably similar to those of free-flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Vision-controlled jetting for composite systems and robots.

Recreating complex structures and functions of natural organisms in a synthetic form is a long-standing goal for humanity1. The aim is to create actuated systems with high spatial resolutions and complex material arrangements that range from elastic to rigid. Traditional manufacturing processes struggle to fabricate such complex systems2. It remains an open challenge to fabricate functional systems automatically and quickly with a wide range of elastic properties, resolutions, and integrated actuation and sensing channels2,3. We propose an inkjet deposition process called vision-controlled jetting that can create complex systems and robots. Hereby, a scanning system captures the three-dimensional print geometry and enables a digital feedback loop, which eliminates the need for mechanical planarizers. This contactless process allows us to use continuously curing chemistries and, therefore, print a broader range of material families and elastic moduli. The advances in material properties are characterized by standardized tests comparing our printed materials to the state-of-the-art. We directly fabricated a wide range of complex high-resolution composite systems and robots: tendon-driven hands, pneumatically actuated walking manipulators, pumps that mimic a heart and metamaterial structures. Our approach provides an automated, scalable, high-throughput process to manufacture high-resolution, functional multimaterial systems.

Injectable tissue prosthesis for instantaneous closed-loop rehabilitation.

To construct tissue-like prosthetic materials, soft electroactive hydrogels are the best candidate owing to their physiological mechanical modulus, low electrical resistance and bidirectional stimulating and recording capability of electrophysiological signals from biological tissues1,2. Nevertheless, until now, bioelectronic devices for such prostheses have been patch type, which cannot be applied onto rough, narrow or deep tissue surfaces3-5. Here we present an injectable tissue prosthesis with instantaneous bidirectional electrical conduction in the neuromuscular system. The soft and injectable prosthesis is composed of a biocompatible hydrogel with unique phenylborate-mediated multiple crosslinking, such as irreversible yet freely rearrangeable biphenyl bonds and reversible coordinate bonds with conductive gold nanoparticles formed in situ by cross-coupling. Closed-loop robot-assisted rehabilitation by injecting this prosthetic material is successfully demonstrated in the early stage of severe muscle injury in rats, and accelerated tissue repair is achieved in the later stage.

Accommodating unobservability to control flight attitude with optic flow.

Attitude control is an essential flight capability. Whereas flying robots commonly rely on accelerometers1 for estimating attitude, flying insects lack an unambiguous sense of gravity2,3. Despite the established role of several sense organs in attitude stabilization3-5, the dependence of flying insects on an internal gravity direction estimate remains unclear. Here we show how attitude can be extracted from optic flow when combined with a motion model that relates attitude to acceleration direction. Although there are conditions such as hover in which the attitude is unobservable, we prove that the ensuing control system is still stable, continuously moving into and out of these conditions. Flying robot experiments confirm that accommodating unobservability in this manner leads to stable, but slightly oscillatory, attitude control. Moreover, experiments with a bio-inspired flapping-wing robot show that residual, high-frequency attitude oscillations from flapping motion improve observability. The presented approach holds a promise for robotics, with accelerometer-less autopilots paving the road for insect-scale autonomous flying robots6. Finally, it forms a hypothesis on insect attitude estimation and control, with the potential to provide further insight into known biological phenomena5,7,8 and to generate new predictions such as reduced head and body attitude variance at higher flight speeds9.

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.

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Expanding our global testing capacity is critical to preventing and containing pandemics1-9. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are required10-14. Pooled testing can be extremely efficient if the pooling strategy is based on local viral prevalence15-20; however, it requires automation, small sample volume handling and feedback not available in current bulky, capital-intensive liquid handling technologies21-29. Here we use a swarm of millimetre-sized magnets as mobile robotic agents ('ferrobots') for precise and robust handling of magnetized sample droplets and high-fidelity delivery of flexible workflows based on nucleic acid amplification tests to overcome these limitations. Within a palm-sized printed circuit board-based programmable platform, we demonstrated the myriad of laboratory-equivalent operations involved in pooled testing. These operations were guided by an introduced square matrix pooled testing algorithm to identify the samples from infected patients, while maximizing the testing efficiency. We applied this automated technology for the loop-mediated isothermal amplification and detection of the SARS-CoV-2 virus in clinical samples, in which the test results completely matched those obtained off-chip. This technology is easily manufacturable and distributable, and its adoption for viral testing could lead to a 10-300-fold reduction in reagent costs (depending on the viral prevalence) and three orders of magnitude reduction in instrumentation cost. Therefore, it is a promising solution to expand our testing capacity for pandemic preparedness and to reimagine the automated clinical laboratory of the future.

The rise of intelligent matter.

Artificial intelligence (AI) is accelerating the development of unconventional computing paradigms inspired by the abilities and energy efficiency of the brain. The human brain excels especially in computationally intensive cognitive tasks, such as pattern recognition and classification. A long-term goal is de-centralized neuromorphic computing, relying on a network of distributed cores to mimic the massive parallelism of the brain, thus rigorously following a nature-inspired approach for information processing. Through the gradual transformation of interconnected computing blocks into continuous computing tissue, the development of advanced forms of matter exhibiting basic features of intelligence can be envisioned, able to learn and process information in a delocalized manner. Such intelligent matter would interact with the environment by receiving and responding to external stimuli, while internally adapting its structure to enable the distribution and storage (as memory) of information. We review progress towards implementations of intelligent matter using molecular systems, soft materials or solid-state materials, with respect to applications in soft robotics, the development of adaptive artificial skins and distributed neuromorphic computing.

Bubble casting soft robotics.

Inspired by living organisms, soft robots are developed from intrinsically compliant materials, enabling continuous motions that mimic animal and vegetal movement1. In soft robots, the canonical hinges and bolts are replaced by elastomers assembled into actuators programmed to change shape following the application of stimuli, for example pneumatic inflation2-5. The morphing information is typically directly embedded within the shape of these actuators, whose assembly is facilitated by recent advances in rapid prototyping techniques6-11. Yet, these manufacturing processes have limitations in scalability, design flexibility and robustness. Here we demonstrate a new all-in-one methodology for the fabrication and the programming of soft machines. Instead of relying on the assembly of individual parts, our approach harnesses interfacial flows in elastomers that progressively cure to robustly produce monolithic pneumatic actuators whose shape can easily be tailored to suit applications ranging from artificial muscles to grippers. We rationalize the fluid mechanics at play in the assembly of our actuators and model their subsequent morphing. We leverage this quantitative knowledge to program these soft machines and produce complex functionalities, for example sequential motion obtained from a monotonic stimulus. We expect that the flexibility, robustness and predictive nature of our methodology will accelerate the proliferation of soft robotics by enabling the assembly of complex actuators, for example long, tortuous or vascular structures, thereby paving the way towards new functionalities stemming from geometric and material nonlinearities.

Viscoelastic control of spatiotemporal order in bacterial active matter.

Active matter consists of units that generate mechanical work by consuming energy1. Examples include living systems (such as assemblies of bacteria2-5 and biological tissues6,7), biopolymers driven by molecular motors8-11 and suspensions of synthetic self-propelled particles12-14. A central goal is to understand and control the self-organization of active assemblies in space and time. Most active systems exhibit either spatial order mediated by interactions that coordinate the spatial structure and the motion of active agents12,14,15 or the temporal synchronization of individual oscillatory dynamics2. The simultaneous control of spatial and temporal organization is more challenging and generally requires complex interactions, such as reaction-diffusion hierarchies16 or genetically engineered cellular circuits2. Here we report a simple technique to simultaneously control the spatial and temporal self-organization of bacterial active matter. We confine dense active suspensions of Escherichia coli cells and manipulate a single macroscopic parameter-namely, the viscoelasticity of the suspending fluid- through the addition of purified genomic DNA. This reveals self-driven spatial and temporal organization in the form of a millimetre-scale rotating vortex with periodically oscillating global chirality of tunable frequency, reminiscent of a torsional pendulum. By combining experiments with an active-matter model, we explain this behaviour in terms of the interplay between active forcing and viscoelastic stress relaxation. Our findings provide insight into the influence of bacterial motile behaviour in complex fluids, which may be of interest in health- and ecology-related research, and demonstrate experimentally that rheological properties can be harnessed to control active-matter flows17,18. We envisage that our millimetre-scale, tunable, self-oscillating bacterial vortex may be coupled to actuation systems to act a 'clock generator' capable of providing timing signals for rhythmic locomotion of soft robots and for programmed microfluidic pumping19, for example, by triggering the action of a shift register in soft-robotic logic devices20.

Ethics and responsibility in biohybrid robotics research.

The industrial revolution of the 19th century marked the onset of an era of machines and robots that transformed societies. Since the beginning of the 21st century, a new generation of robots envisions similar societal transformation. These robots are biohybrid: part living and part engineered. They may self-assemble and emerge from complex interactions between living cells. While this new era of living robots presents unprecedented opportunities for positive societal impact, it also poses a host of ethical challenges. A systematic, nuanced examination of these ethical issues is of paramount importance to guide the evolution of this nascent field. Multidisciplinary fields face the challenge that inertia around collective action to address ethical boundaries may result in unexpected consequences for researchers and societies alike. In this Perspective, we i) clarify the ethical challenges associated with biohybrid robotics, ii) discuss the need for and elements of a potential governance framework tailored to this technology; and iii) propose tangible steps toward ethical compliance and policy formation in the field of biohybrid robotics.

Bioinspired multiscale adaptive suction on complex dry surfaces enhanced by regulated water secretion.

Suction is a highly evolved biological adhesion strategy for soft-body organisms to achieve strong grasping on various objects. Biological suckers can adaptively attach to dry complex surfaces such as rocks and shells, which are extremely challenging for current artificial suction cups. Although the adaptive suction of biological suckers is believed to be the result of their soft body's mechanical deformation, some studies imply that in-sucker mucus secretion may be another critical factor in helping attach to complex surfaces, thanks to its high viscosity. Inspired by the combined action of biological suckers' soft bodies and mucus secretion, we propose a multiscale suction mechanism which successfully achieves strong adaptive suction on dry complex surfaces which are both highly curved and rough, such as a stone. The proposed multiscale suction mechanism is an organic combination of mechanical conformation and regulated water seal. Multilayer soft materials first generate a rough mechanical conformation to the substrate, reducing leaking apertures to micrometres (~10 µm). The remaining micron-sized apertures are then sealed by regulated water secretion from an artificial fluidic system based on the physical model, thereby the suction cup achieves long suction longevity on complex surfaces but minimal overflow. We discuss its physical principles and demonstrate its practical application as a robotic gripper on a wide range of complex dry surfaces. We believe the presented multiscale adaptive suction mechanism is a powerful unique adaptive suction strategy which may be instrumental in the development of versatile soft adhesion.

Multiple forces facilitate the aquatic acrobatics of grasshopper and bioinspired robot.

Aquatic locomotion is challenging for land-dwelling creatures because of the high degree of fluidity with which the water yields to loads. We surprisingly found that the Chinese rice grasshopper Oxya chinensis, known for its terrestrial acrobatics, could swiftly launch itself off the water's surface in around 25 ms and seamlessly transition into flight. Biological observations showed that jumping grasshoppers use their front and middle legs to tilt up bodies first and then lift off by propelling the water toward the lower back with hind legs at angular speeds of up to 18°/ms, whereas the swimming grasshoppers swing their front and middle legs in nearly horizontal planes and move hind legs less violently (~8°/ms). Force measurement and model analysis indicated that the weight support could be achieved by hydrostatics which are proportionate to the mass of the grasshoppers, while the propulsions for motion are derived from the controlled limb-water interactions (i.e., the hydrodynamics). After learning the structural and behavioral strategies of the grasshoppers, a robot was created and was capable of swimming and jumping on the water surface like the insects, further demonstrating the effectiveness of decoupling the challenges of aquatic locomotion by the combined use of the static and dynamic hydro forces. This work not only uncovered the combined mechanisms responsible for facilitating aquatic acrobatics in this species but also laid a foundation for developing bioinspired robots that can locomote across multiple media.

A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality.

Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.

Bacterial outer membrane vesicle nanorobot.

Autonomous nanorobots represent an advanced tool for precision therapy to improve therapeutic efficacy. However, current nanorobotic designs primarily rely on inorganic materials with compromised biocompatibility and limited biological functions. Here, we introduce enzyme-powered bacterial outer membrane vesicle (OMV) nanorobots. The immobilized urease on the OMV membrane catalyzes the decomposition of bioavailable urea, generating effective propulsion for nanorobots. This OMV nanorobot preserves the unique features of OMVs, including intrinsic biocompatibility, immunogenicity, versatile surface bioengineering for desired biofunctionalities, capability of cargo loading and protection. We present OMV-based nanorobots designed for effective tumor therapy by leveraging the membrane properties of OMVs. These involve surface bioengineering of robotic body with cell-penetrating peptide for tumor targeting and penetration, which is further enhanced by active propulsion of nanorobots. Additionally, OMV nanorobots can effectively safeguard the loaded gene silencing tool, small interfering RNA (siRNA), from enzymatic degradation. Through systematic in vitro and in vivo studies using a rodent model, we demonstrate that these OMV nanorobots substantially enhanced siRNA delivery and immune stimulation, resulting in the utmost effectiveness in tumor suppression when juxtaposed with static groups, particularly evident in the orthotopic bladder tumor model. This OMV nanorobot opens an inspiring avenue to design advanced medical robots with expanded versatility and adaptability, broadening their operation scope in practical biomedical domains.

Support academic access to automated cloud labs to improve reproducibility.

Cloud labs, where experiments are executed remotely in robotic facilities, can improve the reproducibility, accessibility, and scalability of experimental biology. Funding and training programs will enable academics to overcome barriers to adopting such technology.

Ultra-sensitive and resilient compliant strain gauges for soft machines.

Soft machines are a promising design paradigm for human-centric devices1,2 and systems required to interact gently with their environment3,4. To enable soft machines to respond intelligently to their surroundings, compliant sensory feedback mechanisms are needed. Specifically, soft alternatives to strain gauges-with high resolution at low strain (less than 5 per cent)-could unlock promising new capabilities in soft systems. However, currently available sensing mechanisms typically possess either high strain sensitivity or high mechanical resilience, but not both. The scarcity of resilient and compliant ultra-sensitive sensing mechanisms has confined their operation to laboratory settings, inhibiting their widespread deployment. Here we present a versatile and compliant transduction mechanism for high-sensitivity strain detection with high mechanical resilience, based on strain-mediated contact in anisotropically resistive structures (SCARS). The mechanism relies upon changes in Ohmic contact between stiff, micro-structured, anisotropically conductive meanders encapsulated by stretchable films. The mechanism achieves high sensitivity, with gauge factors greater than 85,000, while being adaptable for use with high-strength conductors, thus producing sensors resilient to adverse loading conditions. The sensing mechanism also exhibits high linearity, as well as insensitivity to bending and twisting deformations-features that are important for soft device applications. To demonstrate the potential impact of our technology, we construct a sensor-integrated, lightweight, textile-based arm sleeve that can recognize gestures without encumbering the hand. We demonstrate predictive tracking and classification of discrete gestures and continuous hand motions via detection of small muscle movements in the arm. The sleeve demonstration shows the potential of the SCARS technology for the development of unobtrusive, wearable biomechanical feedback systems and human-computer interfaces.

A biomimetic eye with a hemispherical perovskite nanowire array retina.

Human eyes possess exceptional image-sensing characteristics such as an extremely wide field of view, high resolution and sensitivity with low aberration1. Biomimetic eyes with such characteristics are highly desirable, especially in robotics and visual prostheses. However, the spherical shape and the retina of the biological eye pose an enormous fabrication challenge for biomimetic devices2,3. Here we present an electrochemical eye with a hemispherical retina made of a high-density array of nanowires mimicking the photoreceptors on a human retina. The device design has a high degree of structural similarity to a human eye with the potential to achieve high imaging resolution when individual nanowires are electrically addressed. Additionally, we demonstrate the image-sensing function of our biomimetic device by reconstructing the optical patterns projected onto the device. This work may lead to biomimetic photosensing devices that could find use in a wide spectrum of technological applications.