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Actuators and robots capable of representing surfaces can take various forms, depending on the types of actuators used and their arrangements. In traditional robotic surfaces, the corners on the boundary in the undeformed state remain unchanged, indicating that the number and position of the boundary corners do not vary during deformation. This paper introduces a ring-shaped actuator with three types of bending elements combined with a soap film, demonstrating the existence of robotic surfaces in which the number of boundary corners can change through actuation. We also propose forward and inverse kinematics applicable to such robotic surfaces and present simulation results. These findings suggest that inverse kinematics can be achieved in soft robots constructed with prestressed silicone rubber or fabric, including membrane-like components, stretched over a frame. [ABSTRACT FROM AUTHOR]

The need for fast and accurate analysis of soft robots calls for reduced order models (ROM). Among these, the relative reduction of strain-based ROMs follows the discretization of the strain to capture the configurations of the robot. Based on the geometrically exact variable strain parametrization of the Cosserat rod, we developed a ROM that necessitates a minimal number of degrees of freedom to represent the state of the robot: the Geometric Variable Strain (GVS) model. This model allows the static and dynamic analysis of open-, branched-, or closed-chain soft-rigid hybrid robots, all under the same mathematical framework. This paper presents for the first time the complete GVS modeling framework for a generic hybrid soft-rigid robot. Based on the Magnus expansion of the variable strain field, we developed an efficient recursive algorithm for computing the Lagrangian dynamics of the system. To discretize the soft link, we introduce state- and time-dependent basis, which is the most general form of strain basis. We classify the independent bases into global and local bases. We propose "FEM-like" local strain bases with nodal values as their generalized coordinates. Finally, using four real-world applications, we illustrate the potential of the model developed. We think that the soft robotics community will use the comprehensive framework presented in this work to analyze a wide range of specific robotic systems. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven Koopman modeling framework for globally linearizing highly nonlinear dynamical systems in lifted infinite-dimensional state space. In this framework, three data-driven models are proposed and identified to approximate the infinite-dimensional linear Koopman operator through a method called extended dynamic mode decomposition (EDMD). The implementation of EDMD requires a data set of snap pairs and a dictionary of scalar observables, which affects the accuracy of data-driven modeling. Five basis functions are compared and discussed to illustrate their suitable application scenarios. To verify the Koopman data-driven modeling framework, we apply it to the modeling of soft robotic systems, which is thought to be an extremely difficult task due to the large and continuous deformation of soft materials. Results demonstrate that Koopman linear, bilinear, and nonlinear models for both two-dimensional (2D) and three-dimensional (3D) soft robots are superior to the existing state-space modeling approach by achieving less normalized root mean square error (NRMSE). Among the three Koopman models, the constructed nonlinear model has higher performance than the bilinear model, followed by the linear one. Furthermore, the Monomial and Hermite basis functions are the optimal choices for constructing the Koopman linear, bilinear, and nonlinear models for the investigated 2D and 3D soft robots as they have the same structure when the degree of basis function is chosen less than four. Although the Fourier basis function is expected to outperform the Hermite and Gaussian basis functions in modeling systems with oscillatory motion, it is not a preferable selection in the high dimensional soft robotic modeling in our case due to its computational complexity and tendency to be non-convergent. The Sparse Fourier basis function cannot be regarded as a good choice for modeling soft robots, as it is only suitable for generating models with sparse data. It is worth noting that our findings can lay a solid foundation for the dynamics analysis and precise control of highly nonlinear dynamical systems, like soft robots in the future. [ABSTRACT FROM AUTHOR]

Faster recovery, reduced trauma, and improved patient outcomes drive innovations in minimally invasive surgery (MIS). Notwithstanding significant advancements, traditional MIS tools have been limited in navigating deep anatomical pathways and offering precise control at target sites. Continuum robotics has emerged as a solution, with recent developments enabling greater flexibility and maneuverability in surgical interventions. In this review, we first highlight recent developments in mechanical-continuum robots for traditional minimally invasive surgery and then summarize the current state-of-the-art in steerable catheter-based interventions. We discuss limitations to current approaches and explore the emerging potential of soft robots as a novel strategy to address the challenge of developing versatile, highly articulated flexible tools for minimally invasive surgical interventions. We hope that this review will, on the one hand, provide an introduction and resource for students and researchers alike, and on the other hand, will stimulate discussion vis-à-vis future directions in minimally invasive surgery.

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems. [ABSTRACT FROM AUTHOR]

The fusion of wearable soft robotic actuators and motion-tracking sensors can enhance dance performance, amplifying its visual language and communicative potential. However, the intricate and unpredictable nature of improvisational dance poses unique challenges for existing motion-tracking methods, underscoring the need for more adaptable solutions. Conventional methods such as optical tracking face limitations due to limb occlusion. The use of inertial measurement units (IMUs) can alleviate some of these challenges; however, their movement detection algorithms are complex and often based on fixed thresholds. Additionally, machine learning algorithms are unsuitable for detecting the arbitrary motion of improvisational dancers due to the non-repetitive and unique nature of their movements, resulting in limited available training data. To address these challenges, we introduce a collider-based movement detection algorithm. Colliders are modeled as virtual mass-spring-damper systems with its response related to dynamics of limb segments. Individual colliders are defined in planes corresponding to the limbs' degrees of freedom. The system responses of these colliders relate to limb dynamics and can be used to quantify dynamic movements such as jab as demonstrated herein. One key advantage of collider dynamics is their ability to capture complex limb movements in their relative frame, as opposed to the global frame, thus avoiding drift issues common with IMUs. Additionally, we propose a simplified movement detection scheme based on individual dynamic system response variable, as opposed to fixed thresholds that consider multiple variables simultaneously (i.e., displacement, velocity, and acceleration). Our approach combines the collider-based algorithm with a hashing method to design a robust and high-speed detection algorithm for improvised dance motions. Experimental results demonstrate that our algorithm effectively detects improvisational dance movements, allowing control of wearable, origami-based soft actuators that can change size and lighting based on detected movements. This innovative method allows dancers to trigger events on stage, creating a unique organic aesthetics that seamlessly integrates technology with spontaneous movements. Our research highlights how this approach not only enriches dance performances by blending tradition and innovation but also enhances the expressive capabilities of dance, demonstrating the potential for technology to elevate and augment this art form. [ABSTRACT FROM AUTHOR]

Robotic probe manipulator for echocardography (echo) can potentially reduce cardiac radiologists' physical burden. Echo procedure with industrial robots has wide Range of Motion (RoM) but poses safety risks because the robot may clamp the patient against the bed. Conversely, a soft robotic manipulator for echo has safe contact force but suffers from a limited RoM. Due to COVID-19, cardiac radiologists explored performing echo in the prone-positioned patients, which yielded good-quality images but was difficult to perform manually. From robot design perspective, prone position allows safer robot without clamping issue because all actuators are under the patient with minimal RoM to reach the cardiac windows. In this work, we propose a robotic probe manipulator for echo in the prone position employing a combination of a delta 3D printer and a soft end-effector and investigate its feasibility in a clinical setting. We implemented the robot as a scanner type device in which the probe manipulator scans from under a bed with an opening around the chest area. The doctor controls the robot with a joystick and a keypad while looking at a camera view of the chest area and the ultrasound display as feedback. For the experiments, three doctors and three medical students scanned the parasternal window of the same healthy subject with the robot and then manually. Two expert cardiologists evaluated the captured ultrasound images. All medical personnel could obtain all the required views with the robot, but the scanning time was considerably longer than the manual one. The ultrasound image quality scores of the doctors' group remained constant between manual and robotic scans. However, the image scores of the robotic scan were lower in the students' group. In summary, this work verified the ability to obtain clinically sufficient images in echocardiography in the prone position by expert medical doctors using the proposed robotic probe manipulator. Our robot can be further developed with semi automatic procedure to serve as a platform for safe and ergonomic echocardiography. [ABSTRACT FROM AUTHOR]

Ionic electrochemical actuators, which convert electrical energy into mechanical energy through electrochemical‐induced ion migration, show great potential in biomimetic soft robots. However, their applications are still limited due to the influence of the electrode materials and actuator performance. Here, an MXene/carbon nanotube (CNT) heterostructural electrode‐based ionic actuator is developed and realizes dexterous touch manipulation mimicking humans. In this MXene/CNT heterostructure, one‐dimensional CNTs are chemically interconnected into layered two‐dimensional MXene nanosheets, increasing their interlayer spacing, promoting mechanical stability, and enhancing specific surface area, which facilitates the ion migration and storage as well as electrochemical actuation. Accordingly, the MXene/CNT actuator can output excellent mechanical deformation under 2.5 V voltage, including large peak‐to‐peak deformation (displacement 24 mm, strain 1.54%), wide frequency response (0.1–15 Hz), large force (5 mN) and good cycling stability. The actuators can be used to construct artificial fingers to achieve gentle, multi‐point, variable frequency, and synergistic touching on fragile smartphone screens, including pressing a phone number to make a call and tapping an electronic drum. Especially, this finger can tap the drum at a high frequency (13 Hz), exceeding the tapping frequency that real human fingers can reach, which demonstrates its prospect in human‐computer interaction. [ABSTRACT FROM AUTHOR]

Highlights Silicon carbide (SiC)/shape‐memory polyurethane (SMPU) soft robots possess programmable shapes and dual‐drive capabilities based on electrical and thermal methods. Enhancing the thermal conductivity (TC) of these composite materials effectively enhances the driving performance of the soft robots. In this study, we tune the interfacial thickness between SiC particles and the SMPU polymer matrix to regulate the TC of the composites. The optimized composite exhibits a 244% increase in the in‐plane TC and 153% increase in the out‐of‐plane TC. Furthermore, optimization significantly enhances the speed and efficiency of the soft robots. This study reveals that interfacial thickness is a key factor in regulating interfacial heat transfer, potentially introducing a new approach for reducing interfacial thermal resistance in composite materials. This study contributes to a deeper understanding of interfacial heat‐ transfer mechanisms and establishes a new theoretical framework for designing and fabricating advanced composite materials for soft robots. Interfacial heat‐ transfer mechanism was revealed. Interfacial thickness primarily controls interfacial heat transfer. The in‐plane and out‐of‐plane thermal conductivities of prepared composites were enhanced by 244% and 153%, respectively, by modifying the interfacial thickness. The multifunctional performance of the composites was improved due to microscale mechanisms. [ABSTRACT FROM AUTHOR]

Liquid metal (LM) elastomer composites offer promising potential in soft robotics, wearable electronics, and human‐machine interfaces. Direct ink write (DIW) 3D printing offers a versatile manufacturing technique capable of precise control over LM microstructures, yet challenges such as interfilament void formation in multilayer structures impact material performance. Here, a DIW strategy is introduced to control both LM microstructure and material architecture. Investigating three key process parameters–nozzle height, extrusion rate, and nondimensionalized nozzle velocity–it is found that nozzle height and velocity predominantly influence filament geometry. The nozzle height primarily dictates the aspect ratio of the filament and the formation of voids. A threshold print height based on filament geometry is identified; below the height, significant surface roughness occurs, and above the ink fractures, which facilitates the creation of porous structures with tunable stiffness and programmable LM microstructure. These porous architectures exhibit reduced density and enhanced thermal conductivity compared to cast samples. When used as a dielectric in a soft capacitive sensor, they display high sensitivity (gauge factor = 9.0), as permittivity increases with compressive strain. These results demonstrate the capability to simultaneously manipulate LM microstructure and geometric architecture in LM elastomer composites through precise control of print parameters, while maintaining geometric fidelity in the printed design. [ABSTRACT FROM AUTHOR]

Hydrogels are unique polymer materials that possess hydrophilic chains, allowing them to effectively retain a considerable amount of water within their interstitial structures. The first hydrogel, developed in 1955 by Professor Lim and Wichterle from Prague, was specifically designed for manufacturing contact lenses. Hydrogel has the unique ability to absorb and retain a significant amount of water without dissolving. These gels consist of a three-dimensional (3D) network structure composed of cross-linked polymers. Hydrogels can undergo changes in their properties or behavior in response to different stimuli. There are two main problems addressed when using hydrogels: Firstly, it is imperative to conduct more in vivo research and how they behave after being implanted in humans. Secondly, it's crucial to create new, effective, and ecologically responsible ways to make hydrogels. Hydrogels have emerged as unparalleled vehicles for drug delivery, particularly in the context of brain or spinal cord lesions, heavy metal removal, tissue engineering, biosensor, regeneration, cancer, bioprinting, soft robots, biosensor, photonics, perfumery and food industry. In the future, it will be profitable to focus on the development of more sophisticated biopolymer-based hydrogels, combining natural polymers with elastin-cellulose and elastin-alginate mixes. Such developments would be very helpful in tissue regeneration. [ABSTRACT FROM AUTHOR]

Natural organisms offer a rich source for the construction of soft robots exhibiting autonomous and intelligent behaviors, encompassing attributes like motion, perception, and adaptability to environmental shifts. Drawing inspiration from these biological models, a multitude of soft robots have emerged, each distinguished by unique structures and functionalities enabling diverse actions, including swimming, crawling, swinging, walking, and tumbling. In this review, several soft robots and their motion modes from the perspective of specific native species are addressed. The actuation methods of soft robots are discussed, encompassing chemical, electrical, ultrasonic, optical, and magnetic actuation mechanisms. Furthermore, the application domains of soft robots, encompassing areas such as vessel recanalization, targeted drug delivery, cargo manipulation, and sensing are explored, providing a concise summary of their roles and potentials. The current challenges encountered in this research field are highlighted, and promising directions pertaining to soft robots are emphasized. [ABSTRACT FROM AUTHOR]

Dielectric elastomer actuators (DEAs) face an acknowledged challenge: On the one hand, the majority of elastomers only achieve small electroactive deformation (<20%) in the absence of prestretch; on the other hand, rare elastomers capable of showing large electroactive deformation require relatively complicated processing and chemistry. This work addresses this challenge by fabricating an elastomer with a network of large side groups, which achieves a very large electroactive deformation (218%) without pre‐stretch. This elastomer can be rapidly and massively fabricated within a few min, by polymerizing a commercial monomer with a large alkyl side group. The large side groups in the polymer network repel each other and extend the load‐bearing strands, which results in a pronounced strain‐hardening behavior. This behavior helps the elastomer to get rid of electromechanical instability during actuation and hence to exhibit a large electro‐active deformation, a high energy density (>> human muscle), and a large output force (≈500 times self‐weight). the elastomer capable of manufacturing a soft electroactive gripper is demonstrated with large deformation, large force, and rapid response, which enables grasping fragile objects of various complex shapes in an agile away. [ABSTRACT FROM AUTHOR]

Reconfigurable soft robots exhibit superior flexibility and adaptability when coping with complex environments and variable tasks. However, conventional modular design strategy based on soft actuator modules with specific structure and actuation mode as the basic constructing element for reconfigurable soft robots always has limited reprogrammability or scalability. Here, a hierarchical reconfigurable strategy is reported that not only offers conventional module reconfiguration as the first level to build different robot prototypes, but also provides the elastically‐guided multimodal actuation (contraction, bend, and twist) as the second level which can be reprogrammed to construct different actuator modules. This strategy deepens the modularity to a higher dimensionality and provides more choices for robots to adjust various conformations and functions as needed, for example, a peristalsis robot, an omnidirectional crawling robot, and a soft manipulator can be easily constructed using the module‐level reconfiguration. Moreover, soft manipulators with various preprogrammed deformation trajectories based on the mode reconfiguration are proven to dramatically reduce the operation difficulty and cost in potential applications such as environment detection and human‐robot interaction. This work provides a hierarchical framework for reconfigurable soft robots and may open up a new way for modular design. [ABSTRACT FROM AUTHOR]

The combination of fluidity and metallic conductivity has attracted considerable attention to liquid metal (LM), but its development remains challenging due to enormous surface tension. Here, vinyl‐terminated silicone oil and platinum catalyst are added to LM to reduce its surface tension, which develops a special type of liquid‐metal‐silicone (LMS) ink with a catalyst diffusion effect. Combined with an embedded three‐dimentional (3D) printing method, the LMS ink is printed on the support matrix, and the catalyst diffuses outward along the print path to cure the silicone around it, directly constructing self‐encapsulated conductive composites with excellent conductivity and self‐encapsulated flexible tactile sensors based on triboelectric nanogenerator (TENG). The sensor exhibits excellent sensitivity (0.308 V kPa−1), high linearity (≈0.99), and good durability (over 10 000 cycles). Furthermore, when used in flexible wearable electronics, the sensor demonstrates a good performance with an accuracy of ≈96% in classifying different human postures using a convolutional neural network. Finally, through embedded 3D printing with LMS ink and silicone ink, a somatosensory soft robotic gripper with complex cavity structures is designed and manufactured in one step, achieving the all‐in‐one integration of sensors and actuators. This study shows great application potential in flexible electronics and soft robotic systems. [ABSTRACT FROM AUTHOR]

Recently, soft actuators with the capabilities of stimuli response have attracted great attention and shown potential application prospects in soft robots. The critical factor of soft actuators to realize practical applications is the programmable shape deformations. However, it remains a challenge to develop a simple and versatile method to design a soft actuator with programmable deformations. Herein, we report a programmable graphene oxide (GO)/wax moisture-responsive actuator through water-shaping and heat-welding methods. Diverse actuators with different initial shapes can be achieved by the water-shaping method, which provides the possibility for preparing actuators with various desired shapes. Additionally, more complex 3D configurations of actuators can be programmed by the heat-welding method. As proof-of-concept demonstrations, several soft robots, such as a bionic walking robot, a grasping robot, and a weight-bearing robot, are demonstrated. Certainly, the versatile and simple programming methods of soft actuators hold great potential for intelligent robotics. [ABSTRACT FROM AUTHOR]

The precise control of soft and continuum robots requires knowledge of their shape, which has, in contrast to classical rigid robots, infinite degrees of freedom. To partially reconstruct the shape, proprioceptive techniques use built‐in sensors, resulting in inaccurate results and increased fabrication complexity. Exteroceptive methods so far rely on expensive tracking systems with reflective markers placed on all components, which are infeasible for deformable robots interacting with the environment due to marker occlusion and damage. Here, a regression approach is presented for three‐dimensional key point estimation using a convolutional neural network. The proposed approach uses data‐driven supervised learning and is capable of online markerless estimation during inference. Two images of a robotic system are captured simultaneously at 25 Hz from different perspectives and fed to the network, which returns for each pair the parameterized key point or piecewise constant curvature shape representations. The proposed approach outperforms markerless state‐of‐the‐art methods by a maximum of 4.5% in estimation accuracy while being more robust and requiring no prior knowledge of the shape. Online evaluations on two types of soft robotic arms and a soft robotic fish demonstrate the method's accuracy and versatility on highly deformable systems. [ABSTRACT FROM AUTHOR]

Origami, the art of paper folding, has emerged as a versatile technique for crafting intricate 3D structures from 2D sheets. Combined with the magnetic actuation, origami paper becomes the building blocks for cost‐effective, wirelessly controllable magnetic robots. Herein, a biodegradable magnetic paper with excellent formability and recyclability is developed, facilitating its convenient utilization and disposal. The programable magnetic paper, fabricated with specific magnetization and crease patterns, enables the transformation of 2D sheets into predetermined 3D structures. Leveraging the lightweight and pliable nature of paper‐based materials, exceptional control of origami robots with fast response is demonstrated, enabling a wide range of locomotion. Furthermore, the paper‐based approach enables the incorporation of electronic functionality into magnetic actuators. By introducing conductive nanoparticles into magnetic paper, an electrically conductive substance is created. Constructing electronic circuits and integrating electronic components onto the paper‐based printed circuit board platform enables the repairing of broken circuits inside complicated equipment and optical sensing of surrounding environments in conjunction with locomotive robots. The origami robots have a huge potential to be facilitated in diverse fields with various functions, demonstrating complex locomotion, and integrating chemical, optical, thermal, and mechanical sensors for monitoring environmental conditions in hard‐to‐reach locations. The array of possibilities holds significant promise for the widespread application of these origami magnetic robots across a diverse spectrum of research fields in soft robotics. [ABSTRACT FROM AUTHOR]

As a new class of robots, soft continuum manipulators have attracted attention due to their flexibility and compliance. However, these characteristics create challenges for precise modeling and control. This study proposes a hybrid offline and online data‐driven scheme to achieve high‐precision tracking control of a soft continuum manipulator. First, a novel multiscale deep neural network learns the manipulator model offline. Specifically, the feature fusion module extracts highly discriminative features and captures long‐term dependencies from the temporal trajectory data. The self‐attention module strengthens the ability to represent fusion features and enhances the model prediction accuracy. Then, the learnt model is updated using multisensor data online, and the proposed controller further compensates for the updated model and enhances the tracking accuracy in the movement stage. Finally, the experimental results demonstrate a significant improvement in motion accuracy under different trajectory‐tracking scenarios (i.e., deviations of <1 mm in position and <0.8° in orientation). The example of the multiwire cable sorting proves the feasibility of the proposed scheme in high‐precision industrial applications. [ABSTRACT FROM AUTHOR]

Endowing tactile feedback for prosthetic hands is profound for upper‐limb amputees. However, existing prosthetic hands are generally not in possession of the embedded sensory feedback. Herein, a flexible tactile sensor array which can be integrated into an untethered soft prosthetic hand to achieve static and dynamic discrimination tasks is presented. The flexible piezoresistive sensory arrays with 25 sensor units which can be arranged on five fingers of the soft prosthetic hand are fabricated. According to the collected large‐scale tactile dataset (including pressure distribution and pressure magnitude) during different grasping tasks, a learning‐based classification model that can reveal the correspondences between tactile information and object attributes while interacting with touched objects is developed. To transfer tactile information extracted from tactile sensor arrays, a wearable vibrotactile feedback band with a spatial coding feedback strategy is implemented by selectively activating vibrotactile motors located on the skin of the upper arm. In a set of tests performed by an individual with transradial amputation and eight able‐bodied subjects, the soft prosthetic hand integrated with tactile sensor arrays can help the users regain finger tactile sensation, discriminate grasped objects, and achieve real‐time dynamic rolling detection. [ABSTRACT FROM AUTHOR]

Abstract Soft capacitive sensors are widely utilized in wearable devices, flexible electronics, and soft robotics due to their high sensitivity. However, they may suffer delamination and/or debonding due to their low interfacial toughness. In addition, they usually exhibit a small measurement range resulting from their limited stiffness variation range. In this paper, soft silicone‐based capacitive sensors are developed by using a customized multimaterial 3D printer. By curing silicone materials simultaneously, the continuous conductive and dielectric layers achieve a substantial interfacial toughness of 1036 J·m−2. The sensor with tilted thin‐plate dielectrics exhibits interfacial toughness of 645 J·m−2 or 339 J·m−2 in the transverse or longitudinal direction, respectively. Additionally, the sensors demonstrate a broad measurement range from 0.85 Pa to 5000 kPa. This extended range is facilitated by the significant stiffness variation of the separated tilted thin‐plate dielectrics, ranging from 0.56 kPa to 19.76 MPa. Two applications of these fully printed soft sensors, including an intelligent sensorized insole and a robotic hand combining both soft actuators and soft sensors are showcased. It is believed that the strategy, employing 3D printing for soft microstructured sensors, is a general approach not only applicable for improving the performance of soft sensors, but also conducive to designing powerful soft functional devices.

This paper details the design and preliminary demonstrations for a compact climbing robot named EEWOC (Extended-reach Enhanced Wheeled Orb for Climbing). This novel platform utilizes the EEMMMa limb (Elastic Extending Mechanism for Mobility and Manipulation), detailed in previous work. This highly extendable and bendable robotic limb utilizes a unique tape spring structure for long reach in a small, lightweight package. EEWOC combines this limb with additional degrees of freedom and two magnetic grippers to allow it to ascend vertical metal surfaces by consecutively extending and gripping. It is also equipped with wheels for horizontal mobility. A key advantage of this system is EEWOC's ability to bend to place its grippers around obstacles or corners and above ledges. The prototype is small and lightweight, with a profile of 25x30x30 cm and weight of 1.8 kg, while able to extend its limb up to 1.2 m away. With versatile movement options, EEWOC has the potential to fully traverse large metal structures such as ships or buildings for use in inspection tasks. This paper presents a detailed view of the overall system and mechanism design, and successful climbing demonstrations are shown on steel structures. The paper concludes by detailing EEWOC's future capabilities and additional tests and theories needed to refine its maneuvers and control.

Abstract: Conventional mobile robots have difficulty navigating highly unstructured spaces such as caves and forests. In these environments, a highly extendable limb could be useful for deploying hooks to climb over terrain, or for reaching hard-to-access sites for sample collection. This article details a new form of a multimodal mobile robot that utilizes a novel tape spring limb named EEMMMa (elastic extending mechanism for mobility and manipulation). Its innovative U-shaped tape structure allows it to handle loads in tension as well as compression. It can also bend using mechanical multiplexing for a lightweight and compact design that is well suited for mobile robots. For mobility, the limb can extend prismatically to deploy grappling hook anchors to suspend and transport the main body, or even serve as legs. For manipulation, the limb can morph its shape to bend around or over obstacles, allowing it to retrieve distant objects or position cameras around corners. The EEMMMa-1 prototype detailed in this article successfully demonstrates climbing ladders and shelves in 1.5 body lengths per second, and can bend up to 100 deg. A simplified model of the bending kinematics is developed and analyzed. This article concludes by detailing future EEMMMa applications and theories to strengthen the model in future studies.

Traditional robotic devices are often bulky and rigid, making it difficult for them to adapt to the soft and complex shapes of the human body. In stark contrast, soft robots, as a burgeoning class of robotic technology, showcase exceptional flexibility and adaptability, positioning them as compelling contenders for a diverse array of applications. High-performance electrically responsive artificial muscle materials (ERAMMs), as key driving components of soft robots, can achieve efficient motion and deformation, as well as more flexible and precise robot control, attracting widespread attention. This paper reviews the latest advancements in high-performance ERAMMs and their applications in the field of soft robot actuation, using ionic polymer-metal composites and dielectric elastomers as typical cases. Firstly, the definition, characteristics, and electro-driven working principles of high-performance ERAMMs are introduced. Then, the material design and synthesis, fabrication processes and optimization, as well as characterization and testing methods of the ERAMMs are summarized. Furthermore, various applications of two typical ERAMMs in the field of soft robot actuation are discussed in detail. Finally, the challenges and future directions in current research are analyzed and anticipated. This review paper aims to provide researchers with a reference for understanding the latest research progress in high-performance ERAMMs and to guide the development and application of soft robots. • Inspired by the good performance of natural muscles, extensive attention has been paid to the study of artificial muscles. Based on the structure and properties of artificial muscles, the research progress of high-performance artificial muscle materials is systematically reviewed, the working principle of the device-driven deformation is comprehensively analyzed, and the material design, preparation process and characterization methods are deeply analyzed. • The opportunities and challenges of high-performance artificial muscle materials, especially ionic polymer-metal composites and dielectric elastomers, are discussed, and their future research directions are proposed, laying the foundation for further innovative research on artificial muscle materials and their application development in the field of soft robot actuation. [Display omitted] [ABSTRACT FROM AUTHOR]

Soft robots, as a new type of robots, are highly flexible and deformable, which can adapt to the needs of tasks in complex environments. However, due to the complex nonlinear behaviors of soft materials and the unpredictable motion of actuators, accurate modeling and development of suitable controllers for soft robots are currently the main challenges for real applications. In this paper, we propose and compare two different modeling approaches to estimating the shape deformation of a two-dimensional pneumatic soft robot (2D-PSR): an analytical model based on the motion and air pressure dynamics and a data-driven model using Koopman operator theory and finite-dimensional approximate realization of the extended dynamic mode decomposition algorithm. The Unscented Kalman Filter (UKF) is applied to the two models to estimate the system state and filter the noises from sensors, respectively. Subsequently, based on the established models, the linear quadratic regulator (LQR) is designed to realize the precise trajectory tracking control of the 2D-PSR under two typical input signals. Both simulation and experimental results show that the proposed LQR control schemes with UKF designed based on the analytical model (A-FL-UKF-LQR) and Koopman linear model (K-UKF-LQR) can achieve the expectations in terms of tracking accuracy and robustness, in which the K-UKF-LQR framework outperforms the A-FL-UKF-LQR to a certain degree. [ABSTRACT FROM AUTHOR]

In the realm of underwater exploration and operations, soft robots exhibit considerable application potential due to their capacity for agile and complex deformations as well as their inherent compliance. These characteristics grant them excellent environmental adaptability and reduce damage to delicate samples and organisms. Nonetheless, existing underwater soft robots are primarily designed to mimic the movements of marine organisms or for specific functions, and little attention is paid to the camouflage ability. To address these challenges, in this study, a reconfigurable transparent soft robot with variable stiffness for underwater operations is presented. The design and fabrication methodology of the robot module is presented, followed by the kinematic analysis and stiffness characterization. Leveraging the proposed robot module, a soft manipulator and a soft gripper are designed for underwater operations. The soft manipulator excels in underwater pipeline detection and obstacle avoidance, while the soft gripper showcases considerable load‐bearing capacity (about 71 times its weight), making it suitable for tasks such as retrieving aquatic biological samples or garbage fishing. The proposed reconfigurable soft robot demonstrates robust camouflage capabilities, high environmental adaptability, and notable versatility, suggesting potential solutions to existing challenges in the field of underwater exploration. [ABSTRACT FROM AUTHOR]

Soft robotics, an emerging field that focuses on the development of robots utilizing soft, flexible, and deformable materials, is revolutionizing traditional robotics (reliant on rigid materials and motors) and broadening its range of applications and potential uses. In addition, by emulating the structure, function, and characteristics of biological systems, bioinspired materials are facilitating significant progress in a diverse array of soft robotic applications. This review offers an overview of bioinspired materials employed in soft robotics, exploring their potential applications, challenges, and future research directions. For an intuitive understanding, soft robots based on the primary abilities required and the habitats (terrestrial, aquatic, aerial) of the animals and plants they mimic are categorized. Furthermore, real‐world applications of developed soft robots in everyday human life are presented. The novel category classification and comprehensive analysis presented in this review provide insights into the development of soft robotic systems with the potential to transform various industries and enhance quality of life. [ABSTRACT FROM AUTHOR]

Inflatable multistable materials have significantly advanced the design of shape‐preserving soft robotic arms, offering substantial benefits in terms of shape adaptability, energy efficiency, and safety, ensuring operational reliability even in the event of sudden power loss. However, existing strategies for realizing multistable arms often limit themselves to a single mode of multistability, commonly with rotationally symmetric designs favoring extension stability and asymmetric designs inducing bending stability. To address the limitation, this study introduces a pioneering platform termed multimodal multistability that utilizes geometrical frustration. A single cylindrical symmetric cell, designed for extension bistability, could achieve frustrated multistable states in bending by controlling the cell with multiple degrees of freedom incorporated pneumatic actuator. This platform extends the spectrum of attainable stable trajectories while preserving essential attributes of arms, such as load‐bearability, programmability, and reversibility of shape changes. Leveraging a pneumatic system with four degrees of freedom for pressure control, not only enables capturing previously unexplored stable configurations in mechanical metastructures but also allows for the control of their deformation modes. With applications spanning space exploration, medical instruments, and rescue missions, the multimodal multistability promises unparalleled flexibility and efficiency in the design and operation of soft robots. [ABSTRACT FROM AUTHOR]

Soft and tensegrity structures are two configurations that have appeared as robots continue to draw inspiration from nature and diversify beyond rigid machines toward compliant systems. One artificial manifestation of a biological attribute that is an active research topic is the body's capacity to calibrate its stiffness for adapting its behavior to a given task. This study brings together these designs spaces and presents a soft tensile element named FlexiStiff for tensegrity structures to enable transitioning between flexible and stiff states for variable load‐bearing capability and compliance. The device's tensile stiffness constant can be increased by 4400% with a change in pressure. It can provide a high blocking force of 535.5 N and can endure elongation up to 184%. It is assembled using four commercially available materials and a two‐step fabrication method consisting of 3D printing and elastomer curing. As opposed to classical tensegrities for which shape change is inexpensive in terms of energy, this work betokens a new stage in their design wherein the arrangement can radically alter the magnitude of its demand for external energy for shape morphing, a crucial characteristic for operation in partially mapped environments that present diverse terrains and disturbances of varying intensities prompting adaptability. [ABSTRACT FROM AUTHOR]

Magnetic liquid metal (MLM) is a mixture of magnetic particles with gallium‐based liquid metals which utilizes an unconventional combination of fluidity, high thermal/electrical conductivity, biocompatibility, and magnetism. Recently, from materials to applications, studies on MLMs have drastically increased. Single or multiple MLMs can be precisely positioned or can act as a carrier for handling other objects. MLMs are also used in biomedical applications such as cancer treatment by hyperthermia and precision delivery of cancer drugs on tumors, or antibacterial coating which kills bacteria. In electronics applications, MLMs are used for magnetic field‐driven patterning of metallic lines, reconfigurable interconnects, electronic tattoos, and reconfigurable electromagnetic wave shielding. Phase change (solid/liquid) of MLMs adds another unique capability, morphing. A combination of innovations in the micro/nano robots and MLMs has huge potential to bring an unprecedented disruptive technology for a wide variety of applications including self‐morphing shape‐recovery robots, highly localized cancer treatment, and reconfigurable stealth/camouflage, among others. This article comprehensively reviews recent developments in MLMs from the materials to methods of preparation, locomotion of MLMs, their applications, and future outlooks. [ABSTRACT FROM AUTHOR]

Soft pneumatic joint actuators show great potential in applications such as medical machinery, wearable devices, and soft grippers due to their inherent compliance. However, due to the internal friction and periodic relaxation of the elastic materials, the output force of soft pneumatic joint actuators has complex hysteresis characteristics, which seriously affects their control accuracy. To address the asymmetry hysteresis of actuator output force, a neural network model combining a bidirectional long-short-term memory network (BiLSTM) and a multilayer perceptron (MLP) is proposed. The MLP serves as the output layer of the BiLSTM, which is utilized to capture the time dependency of the actuator output force. By applying further nonlinear transformations, the feature representation of the BiLSTM output is retrieved and merged, improving the prediction and generalization capabilities of the model. The experimental results show that the BiLSTM-MLP model has a maximum output force error of only 0.306 N, an average error of less than 0.08 N, and a goodness of fit more than 0.999. Compared with the MLP, LSTM, BiLSTM, and improved PI models, the BiLSTM-MLP model can have higher prediction accuracy, better characterize the hysteresis properties of soft joint actuators, and provides a promising approach for hysteresis modeling of various elastomer actuators. [ABSTRACT FROM AUTHOR]

Soft robots can adaptively interact with unstructured environments. However, nonlinear soft material properties challenge modeling and control. Learning‐based controllers that leverage efficient mechanical models are promising for solving complex interaction tasks. This article develops a closed‐loop pose/force controller for a dexterous soft manipulator enabling dynamic pushing tasks using deep reinforcement learning. Force tests investigate the mechanical properties of a soft robot module, resulting in orthogonal forces of 9−13$9 - 13$ N. Then, the policy is trained in simulation leveraging a dynamic Cosserat rod model of the soft robot. Domain randomization mitigate the sim‐to‐real gap while careful reward engineering induced pose and force control even without explicit force inputs. Despite the approximate simulation, the sim‐to‐real transfer achieved an average reaching distance of 34±14$34 \pm 14$ mm (8.1%L±3.4%L$ L \pm L$), an average orientation error of 0.40±0.29$0.40 \pm 0.29$ rad (23°±17°$\left(23\right)^{\circ} \pm \left(17\right)^{\circ}$) and applied pushing forces up to 3$3$ N. Such performance is reasonable for the intended assistive tasks of the manipulator. The experiments uncovered that the soft robot interacting with the environment exhibited torsional and counter‐balancing movements. Although not explicitly enforced, they emerged from the mechanical intelligence of the manipulator. The results demonstrate the potential of soft robotic manipulation via reinforcement learning. [ABSTRACT FROM AUTHOR]

Herein, the design, modeling, and validation of high‐flow, fluid‐driven, membrane valves tailored specifically for applications in soft robotic systems are described. Targeting the piping problem in hyper‐actuated soft robots, two fluid‐driven membrane valve designs that can admit flows of up to 871 mg s−1$871 \textrm{ } \textrm{ } \text{mg} \textrm{ } \left(\text{s}\right)^{- 1}$ while weighing less than 20 g$false$ are introduced. A mathematical model to predict fluid flow by representing the displacement of the membrane as a scalar quantity influenced by the balance of pressures applied across the valve's ports is established. The model incorporates six parameters with direct physical relevance, enhancing its usefulness in valve design and system integration. In an experimental validation, flow rates with deviations within 4% are predicted and the onset of flow is correctly identified with an error rate of less than 1%. In addition, applications of these valves for flow amplification and for the creation of a fluid‐driven oscillator are experimentally demonstrated. This research contributes to the advancement of soft robotics by providing a tool for designing, optimizing, and controlling fluid‐driven systems and it lays the groundwork for the future development of embedded, fluid‐controlled valve networks that can be used to realize hyper‐actuated soft robotic systems. [ABSTRACT FROM AUTHOR]

Soft robots have been advancing rapidly, but their control is still limited by rigid control elements. Soft valves offer a solution to this problem by enabling soft robots to no longer rely on rigid control elements. They have become an emerging research topic in soft robotics. However, with a large number of publications on soft valves, it may be challenging for researchers to quickly grasp the advanced technology related to soft valves. To address this issue, this article summarizes the current state of development in soft valves. The design principles and applications of soft valves in terms of structures and materials are discussed, along with the modeling ideas for soft valves. Finally, the current challenges faced by soft valves are outlined, and potential solutions to these problems are proposed. [ABSTRACT FROM AUTHOR]

Engineering systems that leverage the flexibility and softness of soft materials have been fostering revolutionary progress and broad interest across various applications. The inherently flexible mechanical properties of these materials lay the groundwork for engineering systems that can adapt comparably to biological organisms, enabling them to adjust to unpredictable environments effectively. However, alongside the positive benefits of softness, these systems face challenges such as low durability, continuous energy demands, and compromised task performance due to the inherently low stiffness of soft materials. These limitations pose significant obstacles to the practical impact of soft engineering systems in the real world beyond innovative concepts. This review presents a strategy that employs materials with variable stiffness to balance adaptability advantages with the challenge of low rigidity. The developments are summarized in materials capable of stiffness modulation alongside their applications in electronics, robotics, and biomedical fields. This focus on stiffness modulation at the material unit level is a critical step toward enabling the practical application of soft engineering systems in real‐world scenarios. [ABSTRACT FROM AUTHOR]