Low-voltage electrohydraulic actuators for untethered robotics.

Rigid robots can be precise but struggle in environments where compliance, robustness to disturbances, or energy efficiency is crucial. This has led researchers to develop biomimetic robots incorporating soft artificial muscles. Electrohydraulic actuators are promising artificial muscles that perform comparably to mammalian muscles in speed and power density. However, their operation requires several thousand volts. The high voltage leads to bulky and inefficient driving electronics. Here, we present hydraulically amplified low-voltage electrostatic (HALVE) actuators that match mammalian skeletal muscles in average power density (50.5 watts per kilogram) and peak strain rate (971% per second) at a 4.9 times lower driving voltage (1100 volts) compared to the state of the art. HALVE actuators are safe to touch, are waterproof, and exhibit self-clearing properties. We characterize, model, and validate key performance metrics of our actuator. Last, we demonstrate the utility of HALVE actuators on a robotic gripper and a soft robotic swimmer.

Robust Learning-Based Control for Uncertain Nonlinear Systems With Validation on a Soft Robot.

Existing modeling and control methods for real-world systems typically deal with uncertainty and nonlinearity on a case-by-case basis. We present a universal and robust control framework for the general class of uncertain nonlinear systems. Our data-driven deep stochastic Koopman operator (DeSKO) model and robust learning control framework guarantee robust stability. DeSKO learns the uncertainty of dynamical systems by inferring a distribution of observables. The inferred distribution is used in our robust and stabilizing closed-loop controller for dynamical systems. We also develop a model predictive control framework with integral action to compensate for run-time parametric uncertainty, such as manipulating unknown objects. Modeling and control experiments in simulation show that our presented framework is more robust and scalable for robotic systems than state-of-the-art controllers using deep Koopman operators and reinforcement learning (RL) methods. We demonstrate that our method resists previously unseen uncertainties, such as external disturbances, at a magnitude of up to five times the maximum control input. Furthermore, we test our DeSKO-based control framework on a real-world soft robotic arm. It shows that our framework outperforms model-based controllers that have full knowledge of the model parameters, and the controller can conduct object pick-and-place tasks without further training. Our approach opens up new possibilities in robustly managing internal or external uncertainty while controlling high-dimensional nonlinear systems in a learning framework. This approach serves as a foundation to greatly simplify high-level control and decision-making for robots.

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.

Perfusable Biohybrid Designs for Bioprinted Skeletal Muscle Tissue.

Engineered, centimeter-scale skeletal muscle tissue (SMT) can mimic muscle pathophysiology to study development, disease, regeneration, drug response, and motion. Macroscale SMT requires perfusable channels to guarantee cell survival, and support elements to enable mechanical cell stimulation and uniaxial myofiber formation. Here, stable biohybrid designs of centimeter-scale SMT are realized via extrusion-based bioprinting of an optimized polymeric blend based on gelatin methacryloyl and sodium alginate, which can be accurately coprinted with other inks. A perfusable microchannel network is designed to functionally integrate with perfusable anchors for insertion into a maturation culture template. The results demonstrate that i) coprinted synthetic structures display highly coherent interfaces with the living tissue, ii) perfusable designs preserve cells from hypoxia all over the scaffold volume, iii) constructs can undergo passive mechanical tension during matrix remodeling, and iv) the constructs can be used to study the distribution of drugs. Extrusion-based multimaterial bioprinting with the inks and design realizes in vitro matured biohybrid SMT for biomedical applications.

Towards A Physics-based Model for Steerable Eversion Growing Robots.

Soft robots that grow through eversion/apical extension can effectively navigate fragile environments such as ducts and vessels inside the human body. This paper presents the physics-based model of a miniature steerable eversion growing robot. We demonstrate the robot's growing, steering, stiffening and interaction capabilities. The interaction between two robot-internal components is explored, i.e., a steerable catheter for robot tip orientation, and a growing sheath for robot elongation/retraction. The behavior of the growing robot under different inner pressures and external tip forces is investigated. Simulations are carried out within the SOFA framework. Extensive experimentation with a physical robot setup demonstrates agreement with the simulations. The comparison demonstrates a mean absolute error of 10 - 20% between simulation and experimental results for curvature values, including catheter-only experiments, sheath-only experiments and full system experiments. To our knowledge, this is the first work to explore physics-based modelling of a tendon-driven steerable eversion growing robot. While our work is motivated by early breast cancer detection through mammary duct inspection and uses our MAMMOBOT robot prototype, our approach is general and relevant to similar growing robots.

Hydroelastomers: soft, tough, highly swelling composites.

Inspired by the cellular design of plant tissue, we present an approach to make versatile, tough, highly water-swelling composites. We embed highly swelling hydrogel particles inside tough, water-permeable, elastomeric matrices. The resulting composites, which we call hydroelastomers, combine the properties of their parent phases. From their hydrogel component, the composites inherit the ability to highly swell in water. From the elastomeric component, the composites inherit excellent stretchability and fracture toughness, while showing little softening as they swell. Indeed, the fracture properties of the composite match those of the best-performing, tough hydrogels, exhibiting fracture energies of up to 10 kJ m-2. Our composites are straightforward to fabricate, based on widely-available materials, and can easily be molded or extruded to form shapes with complex swelling geometries. Furthermore, there is a large design space available for making hydroelastomers, since one can use any hydrogel as the dispersed phase in the composite, including hydrogels with stimuli-responsiveness. These features make hydroelastomers excellent candidates for use in soft robotics and swelling-based actuation, or as shape-morphing materials, while also being useful as hydrogel replacements in other fields.

Will microfluidics enable functionally integrated biohybrid robots?

The next robotics frontier will be led by biohybrids. Capable biohybrid robots require microfluidics to sustain, improve, and scale the architectural complexity of their core ingredient: biological tissues. Advances in microfluidics have already revolutionized disease modeling and drug development, and are positioned to impact regenerative medicine but have yet to apply to biohybrids. Fusing microfluidics with living materials will improve tissue perfusion and maturation, and enable precise patterning of sensing, processing, and control elements. This perspective suggests future developments in advanced biohybrids.

Microfluidic Tissue Engineering and Bio-Actuation.

Bio-hybrid technologies aim to replicate the unique capabilities of biological systems that could surpass advanced artificial technologies. Soft bio-hybrid robots consist of synthetic and living materials and have the potential to self-assemble, regenerate, work autonomously, and interact safely with other species and the environment. Cells require a sufficient exchange of nutrients and gases, which is guaranteed by convection and diffusive transport through liquid media. The functional development and long-term survival of biological tissues in vitro can be improved by dynamic flow culture, but only microfluidic flow control can develop tissue with fine structuring and regulation at the microscale. Full control of tissue growth at the microscale will eventually lead to functional macroscale constructs, which are needed as the biological component of soft bio-hybrid technologies. This review summarizes recent progress in microfluidic techniques to engineer biological tissues, focusing on the use of muscle cells for robotic bio-actuation. Moreover, the instances in which bio-actuation technologies greatly benefit from fusion with microfluidics are highlighted, which include: the microfabrication of matrices, biomimicry of cell microenvironments, tissue maturation, perfusion, and vascularization.

Engineered Magnetic Nanocomposites to Modulate Cellular Function.

Magnetic nanoparticles (MNPs) have various applications in biomedicine, including imaging, drug delivery and release, genetic modification, cell guidance, and patterning. By combining MNPs with polymers, magnetic nanocomposites (MNCs) with diverse morphologies (core-shell particles, matrix-dispersed particles, microspheres, etc.) can be generated. These MNCs retain the ability of MNPs to be controlled remotely using external magnetic fields. While the effects of these biomaterials on the cell biology are still poorly understood, such information can help the biophysical modulation of various cellular functions, including proliferation, adhesion, and differentiation. After recalling the basic properties of MNPs and polymers, and describing their coassembly into nanocomposites, this review focuses on how polymeric MNCs can be used in several ways to affect cell behavior. A special emphasis is given to 3D cell culture models and transplantable grafts, which are used for regenerative medicine, underlining the impact of MNCs in regulating stem cell differentiation and engineering living tissues. Recent advances in the use of MNCs for tissue regeneration are critically discussed, particularly with regard to their prospective involvement in human therapy and in the construction of advanced functional materials such as magnetically operated biomedical robots.

Safe Local Navigation for Visually Impaired Users With a Time-of-Flight and Haptic Feedback Device.

This paper presents ALVU (Array of Lidars and Vibrotactile Units), a contactless, intuitive, hands-free, and discreet wearable device that allows visually impaired users to detect low- and high-hanging obstacles, as well as physical boundaries in their immediate environment. The solution allows for safe local navigation in both confined and open spaces by enabling the user to distinguish free space from obstacles. The device presented is composed of two parts: a sensor belt and a haptic strap. The sensor belt is an array of time-of-flight distance sensors worn around the front of a user's waist, and the pulses of infrared light provide reliable and accurate measurements of the distances between the user and surrounding obstacles or surfaces. The haptic strap communicates the measured distances through an array of vibratory motors worn around the user's upper abdomen, providing haptic feedback. The linear vibration motors are combined with a point-loaded pretensioned applicator to transmit isolated vibrations to the user. We validated the device's capability in an extensive user study entailing 162 trials with 12 blind users. Users wearing the device successfully walked through hallways, avoided obstacles, and detected staircases.

Exploration of underwater life with an acoustically controlled soft robotic fish.

Closeup exploration of underwater life requires new forms of interaction, using biomimetic creatures that are capable of agile swimming maneuvers, equipped with cameras, and supported by remote human operation. Current robotic prototypes do not provide adequate platforms for studying marine life in their natural habitats. This work presents the design, fabrication, control, and oceanic testing of a soft robotic fish that can swim in three dimensions to continuously record the aquatic life it is following or engaging. Using a miniaturized acoustic communication module, a diver can direct the fish by sending commands such as speed, turning angle, and dynamic vertical diving. This work builds on previous generations of robotic fish that were restricted to one plane in shallow water and lacked remote control. Experimental results gathered from tests along coral reefs in the Pacific Ocean show that the robotic fish can successfully navigate around aquatic life at depths ranging from 0 to 18 meters. Furthermore, our robotic fish exhibits a lifelike undulating tail motion enabled by a soft robotic actuator design that can potentially facilitate a more natural integration into the ocean environment. We believe that our study advances beyond what is currently achievable using traditional thruster-based and tethered autonomous underwater vehicles, demonstrating methods that can be used in the future for studying the interactions of aquatic life and ocean dynamics.

A Recipe for Soft Fluidic Elastomer Robots.

This work provides approaches to designing and fabricating soft fluidic elastomer robots. That is, three viable actuator morphologies composed entirely from soft silicone rubber are explored, and these morphologies are differentiated by their internal channel structure, namely, ribbed, cylindrical, and pleated. Additionally, three distinct casting-based fabrication processes are explored: lamination-based casting, retractable-pin-based casting, and lost-wax-based casting. Furthermore, two ways of fabricating a multiple DOF robot are explored: casting the complete robot as a whole and casting single degree of freedom (DOF) segments with subsequent concatenation. We experimentally validate each soft actuator morphology and fabrication process by creating multiple physical soft robot prototypes.

Autonomous Object Manipulation Using a Soft Planar Grasping Manipulator.

This article presents the development of an autonomous motion planning algorithm for a soft planar grasping manipulator capable of grasp-and-place operations by encapsulation with uncertainty in the position and shape of the object. The end effector of the soft manipulator is fabricated in one piece without weakening seams using lost-wax casting instead of the commonly used multilayer lamination process. The soft manipulation system can grasp randomly positioned objects within its reachable envelope and move them to a desired location without human intervention. The autonomous planning system leverages the compliance and continuum bending of the soft grasping manipulator to achieve repeatable grasps in the presence of uncertainty. A suite of experiments is presented that demonstrates the system's capabilities.