Soft Robotics Research Articles

Evaluation of Gait-Assistive Soft Wearable Robot Designs for Wear Comfort, Focusing on Electroencephalogram and Satisfaction

Evaluation of Gait-Assistive Soft Wearable Robot Designs for Wear Comfort, Focusing on Electroencephalogram and Satisfaction

Hopping potential wells and gait switching in a fish-like robot with a bistable tail

Fish outperform current underwater robots in speed, agility, and efficiency of locomotion, in part due to their flexible appendages that are capable of rich combinations of modes of motion. In fish-like robots, actuating many different modes of oscillation of tails or fins can become a challenge. This paper presents a highly underactuated (with a single actuator) fish-like robot with a bistable tail that features a double-well elastic potential. Oscillations of such a tail depend on the frequency and amplitude of excitation, and tuning the frequency-amplitude can produce controllable oscillations in different modes leading to different gaits of the robot. This robot design is inspired by recent work on underactuated flexible swimming robots driven by a single rotor. The oscillations of the rotor can propel and steer the robot, but saturation of the rotor makes performing long turns challenging. This paper demonstrates that by adding geometric bistability to the flexible tail, turns can be performed by controllably exciting single-well oscillations in the tail, while exciting double-well oscillations of the tail produces average straight-line motion. The findings of this paper go beyond the application to a narrow class of fish-like robots. More broadly we have demonstrated the use of periodic excitation to produce bistable response that generate different gaits including a steering gait. The mechanics demonstrated here show the feasibility of applications to other mobile soft robots.

4D printing of liquid crystal elastomer composites with continuous fiber reinforcement

Multifunctional composites have been continuously developed for a myriad of applications with remarkable adaptability to external stimuli and dynamic responsiveness. This study introduces a 4D printing method for liquid crystal elastomer (LCE) composites with continuous fibers and unveils their multifunctional actuation and exciting mechanical responses. During the printing process, the relative motion between the continuous fiber and LCE resin generates shear force to align mesogens and enable the monodomain state of the matrix materials. The printed composite lamina exhibits reversible folding deformations that are programmable by controlling printing parameters. With the incorporation of fiber reinforcement, the LCE composites not only demonstrate high actuation forces but also improved energy absorption and protection capabilities. Diverse shape-changing configurations of 4D composite structures can be achieved by tuning the printing pathway. Moreover, the incorporation of conductive fibers into the LCE matrix enables electrically induced shape morphing in the printed composites. Overall, this cost-effective 4D printing method is poised to serve as an accessible and influential approach when designing diverse applications of LCE composites, particularly in the realms of soft robotics, wearable electronics, artificial muscles, and beyond.

Sim-to-Real of Soft Robots With Learned Residual Physics

Sim-to-Real of Soft Robots With Learned Residual Physics

High-performance magnetic artificial silk fibers produced by a scalable and eco-friendly production method

Flexible magnetic materials have great potential for biomedical and soft robotics applications, but they need to be mechanically robust. An extraordinary material from a mechanical point of view is spider silk. Recently, methods for producing artificial spider silk fibers in a scalable and all-aqueous-based process have been developed. If endowed with magnetic properties, such biomimetic artificial spider silk fibers would be excellent candidates for making magnetic actuators. In this study, we introduce magnetic artificial spider silk fibers, comprising magnetite nanoparticles coated with meso-2,3-dimercaptosuccinic acid. The composite fibers can be produced in large quantities, employing an environmentally friendly wet-spinning process. The nanoparticles were found to be uniformly dispersed in the protein matrix even at high concentrations (up to 20% w/w magnetite), and the fibers were superparamagnetic at room temperature. This enabled external magnetic field control of fiber movement, rendering the material suitable for actuation applications. Notably, the fibers exhibited superior mechanical properties and actuation stresses compared to conventional fiber-based magnetic actuators. Moreover, the fibers developed herein could be used to create macroscopic systems with self-recovery shapes, underscoring their potential in soft robotics applications.

Perovskite nanocrystals photo-initiated in situ encapsulation for optical tracking

Metal halide perovskite (CsPbX3, X = Cl, Br, I) nanocrystals (MHP NCs) have been widely investigated for a variety of optoelectronic applications due to their superior photophysical characteristics. However, the inherent poor stability has limited broad applications. Herein, a facile in situ photopolymerization strategy using MHP NCs as photo-initiators is designed to fabricate homogeneous perovskite-silicone composites with outstanding stability, flexibility, and scalability. The fabrication process is completed upon exposure to 30 W ultraviolet light for 5 min under ambient conditions without additional protections and additives. The composites have exceptional stability in air and can even withstand harsh conditions, such as a basic pH of 13 for six months. The mechanical properties of composites are tunable from rigid to elastic by regulating the composition, ratios of polymerization monomers, and reaction time. Their superb properties enable optical visualization tracking for magnetically driven soft robots. This convenient and effective approach opens a new pathway for future applications in optical tracking, soft displays, biological detection, and bioimaging of perovskite nanocrystals.

Direct Ink Writing 3D Printing Elastomeric Polyurethane Aided by Cellulose Nanofibrils.

3D printing of a flexible polyurethane elastomer is highly demandable for its potential to revolutionize industries ranging from footwear to soft robotics thanks to its exceptional design flexibility and elasticity performance. Nevertheless, conventional methods like fused deposition modeling (FDM) and vat photopolymerization (VPP) polyurethane 3D printing typically limit material options to thermoplastic or photocurable polyurethanes. In this research, a water-borne polyurethane ink was synthesized for direct ink writing (DIW) 3D printing through the incorporation of cellulose nanofibrils (CNFs), enabling direct printing of complex, monolithic elastomeric structures at room temperature that can maintain the designed structure. Additionally, a solvent-induced fast solidification (SIFS) method was introduced to facilitate room-temperature curing and enhance mechanical properties. The 3D-printed WPU structures demonstrated strong interfacial adhesion, exhibiting high ultimate tensile strength of up to 22 MPa and an elongation at break of 951%. The 3D-printed WPU structures also demonstrated outstanding resilience and durability, capable of enduring more than 100 cycles of compression and tension as well as withstanding vehicle crushing and heavy lifting. This method also shows suitability for 3D printing complex structures such as a vase and an octopus.

Self‐Propelled Morphing Matter for Small‐Scale Swimming Soft Robots

AbstractAquatic insects have developed versatile locomotion mechanisms that have served as a source of inspiration for decades in the development of small‐scale swimming robots. However, despite recent advances in the field, efficient, untethered, and integrated powering, actuation, and control of small‐scale robots remains a challenge due to the out‐of‐equilibrium and dissipative nature of the driving physical and chemical phenomena. Here, we have designed small‐scale, bioinspired aquatic locomotors with programmable deterministic trajectories that integrate self‐propelled chemical motors and photoresponsive shape‐morphing structures. A Marangoni motor system is developed integrating structural protein networks that self‐regulate the release of chemical fuel with photochemical liquid crystal network (LCN) actuators that change their shape and deform in and out of the surface of water. While the diffusion of fuel from the motor system regulates the propulsion, the dissipative photochemical deformation of LCNs provides locomotors with control over the directionality of motion at the air‐water interface. This approach gives access to five different but interchangeable modes of locomotion within a single swimming robot via morphing of the soft structure. The proposed design, which mimics the mechanisms of surface gliding and posture change of semiaquatic insects such as water treaders, offers solutions for autonomous swimming soft robots via untethered and orthogonal power and control.

Is Low Polydispersity Always Beneficial? Exploring the Impact of Size Polydispersity on the Microstructure and Rheological Properties of Graphene Oxide.

Graphene oxide (GO) is a promising material widely utilized in advanced materials engineering, such as in the development of soft robotics, sensors, and flexible devices. Considering that GOs are often processed using solution-based methods, a comprehensive understanding of the fundamental characteristics of GO in dispersion states becomes crucial given their significant influence on the ultimate properties of the device. GOs inherently exhibit polydispersity in solution, which plays a critical role in determining the mechanical behavior and flowability. However, research in the domain of 2D colloids concerning the effects of GO's polydispersity on its rheological properties and microstructure is relatively scant. Consequently, gaining a comprehensive understanding of how GO's polydispersity affects these critical aspects remains a pressing concern. In this study, we aim to investigate the dispersions and structure of GOs and clarify the effect of polydispersity on the rheological properties and yielding behavior. Using a rheometer, polarized optical microscopy, and small-angle X-ray scattering, we found that higher polydispersity in the same average size leads to overall improved rheological properties and higher flowability during yielding. Thus, our study can be beneficial in the employment of polydispersity in the processing of GO such as 3D printing and fiber spinning.

Simplified discrete model for axisymmetric dielectric elastomer membranes with robotic applications

Soft robots utilizing inflatable dielectric membranes can realize intricate functionalities through the application of non-mechanical fields. However, given the current limitations in simulations, including low computational efficiency and difficulty in dealing with complex external interactions, the design and control of such soft robots often require trial and error. Thus, a novel one-dimensional (1D) discrete differential geometry (DDG)-based numerical model is developed for analyzing the highly nonlinear mechanics in axisymmetric inflatable dielectric membranes. The model captures the intricate dynamics of these membranes under both inflationary pressure and electrical stimulation. Comprehensive validations using hyperelastic benchmarks demonstrate the model’s accuracy and reliability. Additionally, the focus on the electro-mechanical coupling elucidates critical insights into the membrane’s behavior under varying internal pressures and electrical loads. The research further translates these findings into innovative soft robotic applications, including a spherical soft actuator, a soft circular fluid pump, and a soft toroidal gripper, where the snap-through of electroelastic membrane plays a crucial role. Our analyses reveal that the functional ranges of soft robots are amplified by the snap-through of an electroelastic membrane upon electrical stimuli. This study underscores the potential of DDG-based simulations to advance the understanding of the nonlinear mechanics of electroelastic membranes and guide the design of electroelastic actuators in soft robotics applications.

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Bioinspired soft robotics is an emerging field that aims to develop flexible and adaptive robots inspired by the movement and capabilities of biological organisms. This review article examines recent advances in materials, actuation mechanisms, sensors, and control strategies and discusses the challenges and future prospects of bioinspired soft robotics. Key innovations highlighted include pneumatic, elastomer actuators, variable‐length shape memory alloy tendons, closed‐loop control with soft sensors, and the incorporation of soft materials including shape memory polymers and conductive composites. Challenges in soft robotics such as achieving complex motion control, incorporating feedback systems, modeling soft material dynamics, and replicating biological muscle efficiency with artificial muscles are also discussed. Promising future directions are explored including the integration of biodegradable materials, machine learning‐based control algorithms, and leveraging data‐driven techniques for modeling and control. Building on progress in multi‐functional materials, manufacturing techniques, and bioinspired design principles, soft robots hold considerable promise for expanding robot capabilities, enhancing versatility and adaptability, enabling applications from wearable assistive devices to search and rescue operations. This review provides a holistic perspective encompassing key drivers propelling innovations in the vibrant field of bioinspired soft robotics.

Lignin‐Based Macromolecular Photoinitiator for Non‐Migration, Self‐Adhesive, and Water‐Resistant Eutectogels toward Underwater Reliable Communication

AbstractHydrophobic conductive gels have attracted much attention in underwater sensing as the soft robots and wearable sensors. Among the various methods for preparing conductive gels, UV‐initiated polymerization shows advantages of rapid curing and significant energy savings. However, traditional commonly used photoinitiators in UV‐initiated polymerization often migrate or diffuse within conductive gels, especially with prolonged use or underwater, posing potential environmental and health risks. Herein, a novel lignin‐based macromolecular photoinitiator (L‐BF) is first designed by incorporating benzoylformate into the lignin backbone, demonstrating excellent UV absorption, high radical initiation efficiency, and hydrophobicity. Subsequently, hydrophobic eutectogels (HEG) are prepared via UV‐initiated polymerization using L‐BF as photoinitiator. The HEG shows excellent mechanical properties (toughness of 5.67 MJ m−3 and strain of 941%) and scarcely L‐BF migration underwater. Moreover, the hydrophobic network of L‐BF endowed HEG with hydrophobicity (water contact angle exceeds 110°; swelling ratio is <5.8%), superior underwater adhesion (255 kPa), even maintained excellent sensing performance (gauge factor of 4.69), and long‐term reproducibility (20 000 cycles) in air and underwater. Validation confirms the potential of HEG as an effective wearable sensor for underwater posture monitoring and communication, advancing the use of lignin and low‐migration conductive gels in marine exploration.

Ag-S coordination strategy for high recovery driving stress in recyclable shape memory polymers

To address the issue of low strength and recovery stress in recyclable shape memory polymer (SMP) materials with dynamic covalent bonds in practical applications, we propose a method based on Ag-S coordination interactions to improve dynamic covalent bonds, thereby preparing recyclable SMP with high recovery stress and large recovery strain. The introduction of in situ reduced silver nanoparticles (AgNPs) in the SMP system play multiple roles, serving as additional physical crosslinking points at the microscale and coordinating with disulfide bonds in the system to construct a multi-level dynamic network structure. This endows the material with exceptional mechanical properties (tensile strength of 25.93 MPa and fracture strain of 1466.83 %) and recovery driving stress (5.59 MPa), while maintaining more than 99 % shape recovery and fixity rate. Furthermore, due to the outstanding photothermal performance of AgNPs, the composite material has acquired remote photothermal driving capabilities. The proposed Ag-S coordination enhancement offers a new approach for SMP materials that achieve both large actuation distance and high recovery stress, holding significant potential for applications in soft robotics and actuators.

Modeling and motion analysis of flexible legged robots using the finite particle method

Robotics with flexible legs have attracted significant attention. Engineers often design and analyze the motion of legged robots from kinematic and biomimetic perspective. However, the influence of flexibility of the feet on robot locomotion is often not given sufficient considerations, which is also very crucial to the motion posture of the flexible legged robots, especially as the soft robots design becomes increasingly popular. The mainly difficulties lies in the traditional numerical methods in handling the dynamic motion analysis with both large rigid motion and large deformation. In this paper, the finite particle method (FPM) is used to simulate the motion and deformation coupled problems of the flexible six-legged robot. A shell-based particle model of a six-leg robot and the contact model between legs and ground are built. Without iterative and modification of the FPM analytical framework, structural nonlinearity is efficiently handled after eliminating rigid body motions by a fictitious reverse motion. The motion and deformation of a single leg with varying leg thickness, locomotion speed, and leg-to-ground friction coefficients were simulated. By analyzing the stress distribution in the leg and the number of contact points with the ground, the mechanical leg was optimized in design. Furthermore, the motion and deformation of the entire six-legged robot were simulated using the FPM. The numerical results' feasibility was validated through comparison with experimental data obtained from robot walking tests. The proposed method effectively simulates the motion and deformation of flexible robots, providing significant insights for the design of soft robots.

A fabrication strategy for millimeter-scale, self-sensing soft-rigid hybrid robots.

Soft robots typically involve manual assembly of core hardware components like actuators, sensors, and controllers. This increases fabrication time and reduces consistency, especially in small-scale soft robots. We present a scalable monolithic fabrication method for millimeter-scale soft-rigid hybrid robots, simplifying the integration of core hardware components. Actuation is provided by soft-foldable polytetrafluoroethylene film-based actuators powered by ionic fluid injection. The desired motion is encoded by integrating a mechanical controller, comprised of rigid-flexible materials. The robot's motion can be self-sensed using an ionic resistive sensor by detecting electrical resistance changes across its body. Our approach is demonstrated by fabricating three distinct soft-rigid hybrid robotic modules, each with unique degrees of freedom: translational, bending, and roto-translational motions. These modules connect to form a soft-rigid hybrid continuum robot with real-time shape-sensing capabilities. We showcase the robot's capabilities by performing object pick-and-place, needle steering and tissue puncturing, and optical fiber steering tasks.

Composite Hydrogels with Rapid Self-Healing, Stretchable, Moldable and Antibacterial Properties Based on PVA/ε-Poly-l-lysine/Hyaluronic Acid

Self-healing, stretchable, and moldable hydrogels have a great potential application in tissue engineering and soft robotics. Despite great success in reported hydrogels, it is still a great challenge to construct the moldable hydrogels with an ultrafast self-healing performance. Herein, the composite hydrogels (PBLH) with ultrafast self-healing, stretchable, and moldable properties were successfully constructed by poly (vinyl alcohol) (PVA), borate (B), ε-poly-l-lysine (EPL), and hyaluronic acid (HA) based on an efficient one-pot method. Fourier transform infrared spectroscopy, X-ray diffraction, and rheological measurements confirmed the formation of a dynamic network among PVA, B, EPL, and HA through the cross-linking of dynamic borate bonds, electrostatic interaction, and hydrogen bonding. Having fabricated the dynamic network structure, the damage gap of the composite hydrogels can heal within 1 min, presenting an excellent self-healing ability. Simultaneously, the composite hydrogels can be molded into various shapes, and the length of the composite hydrogels can be stretched to 15 times their original length. In addition, the composite hydrogels exhibited an excellent antibacterial property against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). Our results illustrated that the composite hydrogels not only retain the advantages of traditional hydrogels but also possess ultrafast self-healing, outstanding stretchable and antibacterial properties, presenting a prospective candidate for constructing biomedical materials.

Perspectives on Intelligence in Soft Robotics

Engineers frequently aim to streamline environmental factors to facilitate the effective operation of robots. However, in nature, environmental considerations play a crucial role in shaping the embodiment of organisms. To comply robots with the complexity of real‐world environments, embedding similar intelligence is key. In the field of soft robotics, various approaches offer insight into how intelligence can be integrated into artificial agents. A discussed topic is the intricate relationship between the brain and the body at the core of intelligence in robots. The goal of this article is, therefore, to unravel the strategies to implement different types of intelligence currently adopted in soft robots. A classification is made by making a distinction between agents that adapt to their environment by 1) their adaptive shape, 2) their adaptive functionality, and 3) their adaptive mechanics. Additionally, the perspectives on intelligence based on their computational approach are distinguished: centralized computation, decentralized computation, or embedded computation. It is concluded that a tailored robotic design approach attuned to specific environmental demands is needed. To unlock the full potential of soft robots, a fresh perspective on embodied intelligence is described, so‐called mechanical intelligence, emphasizing the robot's responsiveness to changing external conditions of a real‐world environment.

Sound‐Based Assembly of Magnetically Actuated Soft Robots Toward Enhanced Release of Extracellular Vesicles

Magnetic soft robots have emerged as promising tools in biomedicine due to their wireless actuation, rapid response, and compatibility with biological systems. Despite the various innovative strategies proposed for their fabrication, they suffer from complex processes and limited cellular compatibility. Therefore, there is an urgent need to explore alternative approaches that are fast, mild, and highly tunable. Herein, a novel fabrication strategy for contactless assembly of soft‐robots is introduced for the first time. This technology exploits hydrodynamic instabilities at the free surface of a fluid layer, thus enabling the fabrication of centimeter‐scale robots featuring diverse structural properties. These features show a wide range of deformation modes in response to magnetic fields, including folding, bending, and expanding. Furthermore, the design and assembly of novel actuators with customized shapes as fish‐ and butterfly‐like structures is shown. The fabricated patterns exhibit different modes of motion under the influence of uniform magnetic fields. As a proof of concept, an innovative application of this technology combined with the proposed soft robots is represented by the enhanced release of extracellular vesicles. Altogether, this novel fabrication method along with the newly developed magnetic soft robots enables the manufacturing of high‐performance, multifunctional, and cytocompatible intelligent systems.

Electromechanics of stretchable hybrid response pressure sensors based on porous nanocomposites

Stretchable pressure sensors are a key enabler of human-mimetic e-skin technology, with promising applications in soft robotics, prosthetics, biomimetics, and biosensors. Stretchable hybrid response pressure sensor (SHRPS) is an emerging type of soft pressure sensor that employs hybrid piezoresistive and piezocapacitive responses. A unique feature of SHRPS based on barely conductive porous nanocomposite (PNC) is its exceptional pressure sensitivity which trivializes its sensitivity to lateral stretch or shear. In this work, we experimentally characterize the electromechanical responses of SHRPS under various loading conditions and provide theoretical explanations through an equivalent circuit model. The capacitance and resistance of the PNC are described by a parallel mixing law and Archie’s law, respectively. Our model can reasonably predict the responses of SHRPS. Our findings reveal that SHRPS exhibits minimal sensitivity to stretch and shear because the hybrid response mechanism is activated only under compression. The effects of PNC-electrode contact impedance and fringe effects are discussed.

The Integration of Advanced Mechatronic Systems into Industry 4.0 for Smart Manufacturing

In recent years, the rapid advancement of digital technologies has driven a profound transformation in both individual lives and business operations. The integration of Industry 4.0 with advanced mechatronic systems is at the forefront of this digital transformation, reshaping the landscape of smart manufacturing. This article explores the convergence of digital technologies and physical systems, with a focus on the critical role of mechatronics in enabling this transformation. Using technologies such as advanced robotics, the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, industries are developing intelligent and interconnected systems capable of real-time data exchange, distributed decision making, and automation. The paper further explores two case studies: one on a smart plastic injection moulding machine and another on soft robots. These examples illustrate the synergies, benefits, challenges, and future potential of integrating mechatronics with Industry 4.0 technologies. Ultimately, this convergence fosters the development of smart factories and products, enhancing manufacturing efficiency, adaptability, and productivity, while also contributing to sustainability by reducing waste, optimising resource usage, and lowering the environmental impact of industrial production. This marks a significant shift in industrial production towards more sustainable practices.