Soft Gripper Research Articles

Soft Gripper Design and Fabrication for Underwater Grasping

Underwater manipulation with current robotics technology is a challenging task with significant limits in versatility and robustness terms. Such functionality has tremendous potential covering a broad spectrum of applications, mainly replacing divers performing hazardous jobs. Soft robotics provides an efficient solution for operating in these scenarios and adapting to uncertain environmental conditions. This paper presents the design and fabrication of a simple, low-cost, and easily deployable soft gripper for underwater manipulation. We use modelling and simulation techniques for designing the soft fluidic elastomer actuators that compose the soft gripper and additive manufacturing techniques for rapid test cycles and validation. These techniques allow for a fast redesign depending on the application requirements. The proposal combines materials and fabrication techniques to take advantage of their strengths. We validate the feasibility and ability of the proposed soft gripper in a challenging underwater scenario using a subaquatic vehicle.

A novel design of a passive variable stiffness soft robotic gripper

Inspired by the twisting and hanging phenomenon of vines, this paper proposes and designs a passive variable stiffness soft robotic gripper to grasp an object in a simple and robust manner using the principle of jamming. This method has the characteristics of high reliability and good stability, which can achieve soft grasping and rigid load-bearing of the object. Firstly, according to two key issues, the design model of the gripper is proposed, the principle of the proposed gripper is analyzed, and the relationship between the stiffness of the gripper and the stiffness of the object is revealed. Secondly, the model of the robotic gripper is created using a conventional motor drive method, and the grasping process and deformation causes of the gripper are analyzed by using the principle of instability effect and large deformation principle. Finally, the experimental prototype is developed and the feasibility of the design principle and the grasping deformation process of the gripper are verified by gripping experiments.

An Educational Test Rig for Kinesthetic Learning of Mechanisms for Underactuated Robotic Hands

Teaching robotics requires interdisciplinary skills and a good creativity, providing instructions and hands-on experiences, exploiting different kinds of learning. Two kinds of learning methods are commonly used: the ‘visual learning’ and the ‘auditory learning’, recognizable by the preference of an approach for images, rather than for texts, or oral explanations. A third possible learning style is the ‘kinesthetic learning’, based on tactile activities, which is generally least exploited, both by teachers in the classroom and by students during individual study. In this perspective, the use of educational test rigs is a good practice and adds an opportunity to share a passion for robotics. The paper focuses on the realization and application of an educational test rig aimed at explaining how a differential mechanism works and how it can be applied to robotic underactuated soft grippers to move multiple robotic fingers independently of each other using just a single actuator. The differential test bench was realized by 3D printing and mounted with the help of students in high school seminaries oriented to encourage students towards robotic or mechatronic studies. This activity was very thrilling for the students and helped them to approach robotics in a natural way, exploiting kinesthetic learning as it is demonstrated by test results.

Soft Gripper with Electro-Thermally Driven Artificial Fingers Made of Tri-layer Polymers and a Dry Adhesive Surface.

Soft grippers have attracted great interest in the soft robotics research field. Due to their lack of deformability and control over compliance, it can be challenging for them to pick up objects that are too large or too small in size. In particular, compliant objects are vulnerable to the large grasping force. Therefore, it is crucial to be able to adjust the stiffness of the gripper materials. In this study, a soft gripper consisting of three artificial fingers is reported on. Each of the artificial fingers is made of a tri-layer polymer structure. An exterior layer, made of an ecoflex-graphene composite is embedded with electric wires as a heating source, by applying direct-current potential. The Joule heat not only allows for deformation of the exterior layer, but also transfers heat to the middle layer of the thermoplastic polyurethane (TPU) elastomer. As a result, the stiffness of the TPU layer can be adjusted using electro-thermal heating. Meanwhile, the third layer consists of a polydimethylsiloxane replica as a supporting layer with a gecko-inspired dry adhesive structure. By applying voltage through electric wires, the artificial fingers can bend and, thus, the soft gripper can hold the objects, with the help of the dry adhesive layer. Finally, objects like a shuttlecock, tennis ball and a glass beaker, can be picked up by the soft gripper. This research may provide an insight for the design and fabrication of soft robotic manipulators.

Исследование параметров поворотного актуатора для использования в конструкциях захватов для плодов и овощей

The article is devoted to determining the deviation of the angle of rotation of a soft actuator, depending on the pressure inside it. Several samples were made, which differ in wall thickness. The study was carried out on an experimental pneumatic installation, which has the ability to determine the angle of deviation when pressure is applied. Based on the results obtained, the dependence of the angle of rotation on the pressure inside the cavity and the thickness of the actuator wall was determined. As a result of the studies of twisted actuators, regression equations were obtained, which allow determining the dependence of the angle of rotation on the applied pressure. Keywords: ACTUATOR, PNEUMATIC SOFT GRIP, STEERING ANGLE, SOFT ROBOTICS

Proprioception and Exteroception of a Soft Robotic Finger Using Neuromorphic Vision-Based Sensing.

Equipping soft robotic grippers with sensing and perception capabilities faces significant challenges due to their high compliance and flexibility, limiting their ability to successfully interact with the environment. In this work, we propose a sensorized soft robotic finger with embedded marker pattern that integrates a high-speed neuromorphic event-based camera to enable finger proprioception and exteroception. A learning-based approach involving a convolutional neural network is developed to process event-based heat maps and achieve specific sensing tasks. The feasibility of the sensing approach for proprioception is demonstrated by showing its ability to predict the two-dimensional deformation of three points located on the finger structure, whereas the exteroception capability is assessed in a slip detection task that can classify slip heat maps at a temporal resolution of 2 ms. Our results show that our proposed approach can enable complete sensorization of the finger for both proprioception and exteroception using a single camera without negatively affecting the finger compliance. Using such sensorized finger in robotic grippers may provide safe, adaptive, and precise grasping for handling a wide category of objects.

Magneto-active soft matter with reprogrammable shape-morphing and self-sensing capabilities

Interest in creating soft active matter that can repeatedly undergo shape morphing and self-sensing in response to external stimuli is growing. Magneto-active soft matter (MASM) with untethered, fast, and reversible shape reconfiguration is highly desirable for diverse applications in biomedical devices, wearable devices, soft robotics. In this work, we develop a heat-assisted magnetic reprogramming strategy for fabricating MASMs capable of reprogrammable shape-morphing and self-sensing functions. The magnetic reprogramming strategy is based on heating thermoplastic matrix above its melting point and reorienting soft-magnetic particle chains by applying magnetic fields during cooling. By reprogramming magnetization profiles through particle chain reconstruction of printed architecture, we demonstrate multiple deformation modes with distinct shape-morphing. This magnetic reprogramming approach enabled multiscale and reprogrammable soft machines with the tunable actuation response, such as adaptive grasping of a soft gripper. In addition, in combining with the unique sensing mechanism of triboelectric skin (tribo-skin), the self-sensing performance of MASMs is realized by using electrical signals to identify the deformation and contact behaviors. We anticipate that the magnetic reprogramming strategy and multimaterial 3D printing-assisted technique can open new avenues for the fabrication of multifunctional MASMs.

A Preliminary Study on Grip-Induced Nerve Damage Caused by a Soft Pneumatic Elastomeric Gripper.

Forceps, clamps, and haemostats are essential surgical tools required for all surgical interventions. While they are widely used to grasp, hold, and manipulate soft tissue, their metallic rigid structure may cause tissue damage due to the potential risk of applying excessive gripping forces. Soft pneumatic surgical grippers fabricated by silicone elastomeric materials with low Young’s modulus may offer a promising solution to minimize this unintentional damage due to their inherent excellent compliance and compressibility. The goal of this work is to evaluate and compare the grip-induced nerve damage caused by the soft pneumatic elastomeric gripper and conventional haemostats during surgical manipulation. Twenty-four Wistar rats (male, seven weeks) are subjected to sciatic nerve compression (right hind limb) using the soft pneumatic elastomer gripper and haemostats. A histopathological analysis is conducted at different time-points (Day 0, Day 3, Day 7 and Day 13) after the nerve compression to examine the morphological tissue changes between the rats in the ‘soft gripper’ group and the ‘haemostats’ group. A free walking analysis is also performed to examine the walking function of the rats after recovery from different time points. Comparing the rigid haemostats and soft gripper groups, there is a visible difference in the degree of axonal vacuolar degeneration between the groups, which could suggest the presence of substantial nerve damage in the ‘haemostats’ group. The rats in the haemostats group exhibited reduced right hind paw pressure and paw size after the nerve compression. It shows that the rats tend not to exert more force on the affected right hind limb in the haemostats group compared to the soft gripper group. In addition, the stance duration was reduced in the injured right hind limb compared to the normal left hind limb in the haemostats group. These observations show that the soft pneumatic surgical gripper made of silicone elastomeric materials might reduce the severity of grip-induced damage by providing a safe compliant grip compared to the conventional haemostats. The soft pneumatic elastomer gripper could complement the current surgical gripping tool in delicate tissue manipulation.

Optimal design and experimental validation of 3D printed soft pneumatic actuators

This study develops a novel design of a unit cell-based bending-type soft pneumatic actuator, and formulates the design problem as compliant mechanisms under design-dependent pressure loadings. The proposed design is first optimized by using a topology optimization algorithm, in which the design-dependent loads and fluid-structure interface are tracked and formulated via finite element based approaches. Then, to validate the optimized design, it is modeled numerically using finite element analysis (FEA) and compared with the non-optimized traditional rectangular design. The optimal design can provide 19.5% improvements in bending angle. In addition, the proposed optimal design is prototyped using 3D printing. The prepared single actuator specimens are tested under pneumatic pressure, and the measured deformations are compared with those obtained from FEA. The results reveal that the optimized design can undergo large and compliant deformations under pneumatic pressure and generate a full () bending. Furthermore, multiple actuator specimens of the proposed design are also assembled and integrated to prototype soft pneumatic grippers, with which several grasping tests are conducted. The adaptability and compatibility of the soft gripper are verified via gripping a wide range of irregular, soft, and fragile objects.

Self‐Sensing Robotic Structures from Architectured Particle Assemblies

The tight coupling of shape transformation, stiffness tuning, and self‐sensing that biological organisms exhibit has long served as inspiration for next‐generation soft robots. However, most current soft robots rely on intrinsically soft materials for actuation, separately embedded sensors for sensing, and have fixed stiffness once fabricated. Large gaps remain between these soft robots and biological organisms where multifunctionality is realized within an integrated body. Herein, a new class of robotic structures from architectured particle assemblies is introduced. They combine three functions: shape changing, stiffness variation, and self‐sensing into one monolithic structure. Unlike traditional entirely soft robots, the design utilizes the geometric contacts of stiff, architectured particles under confining pressure to achieve these functions. The applications of these structures by designing smart self‐sensing architectures and soft grippers are demonstrated. The design provides a new paradigm of multifunctional robotic structures, with potential multiscale applications in adaptive robots, smart devices, and reconfigurable architectures.

GSG: A Granary-Shaped Soft Gripper With Mechanical Sensing via Snap-Through Structure

Soft robotic grippers have attracted considerable attention in terms of the advantages of the high compliance and robustness to variance in object geometry; however, they are still limited by the corresponding sensing capabilities. We propose a novel soft gripper that looks like a ‘granary’ in the geometrical shape with a snap-through bistable mechanism fabricated by an ordered mold technology, which consists of a palm chamber, shell, cap and three fingers. It can achieve ‘sensing’ mechanically and perform pinching, enveloping and caging grasps for objects with various profiles. In particular, the snap-through bistable mechanism in the proposed gripper allows us to reduce the complexity of the mechanism, control, and sensing designs. The grasping behavior is activated once the gripper's deformation or perceived pressure arrives at a certain value. First, after the theoretical model for snap-through behavior is constructed, the modularized design of the gripper is described in detail. Then, the ordered molding method is employed to fabricate the proposed gripper. Finally, the finite element (FE) simulations are conducted to verify the built theoretical model. Further, a series of grasping experiments are carried out to assess the performance of the proposed gripper on grasping and sensing. The experimental results illustrate that the proposed gripper can manipulate a variety of soft and rigid objects and remain stable even though it undergoes external disturbances.

A Soft Robotic Gripper With Neutrally Buoyant Jamming Pads for Gentle Yet Secure Grasping of Underwater Objects

Delicate grasping of complex diverse objects is a challenging task for underwater vehicles, such as remotely operated vehicles (ROVs). In this article, a novel controllably compliant soft robotic underwater gripper is presented, which uses two neutrally buoyant particle jamming pads to safely and securely grasp arbitrarily shaped objects, including fragile and/or massive targets. Antagonistic low-friction rolling diaphragm hydraulic cylinders are used to control the compliance of the jaw closure to passively limit the total force applied during the approach. The antagonistic hydraulic cylinders also compensate for the volume reduction of the pads during the jamming process while still enabling rigid grasp during manipulation. Soft finger-like fiber-reinforced actuators are used to maintain the shape of pads without introducing rigid elements. Force limitation is demonstrated by the ability to pick up fragile objects without breakage and to surround soft targets without excessive deformation of the object. We present the overall design, experimental setup, and in-water testing using a compact ROV-based hydraulic drive system. The resulting system has demonstrated capability for grasping a diverse range of objects that vary widely in terms of weight, size, and geometry, largely enabled by the hybrid design of soft grippers guiding jamming pads into optimal configurations.

A Two-Finger Soft Gripper Based on Bistable Mechanism

Soft grippers are widely studied and utilized in soft robotics owing to their advantages in terms of compliance, safety, and adaptability. Limited by the mechanical design and driving methods, their response speed is usually unsatisfactory. To achieve fast and safe grasping, a novel design scheme for a two-finger soft gripper is proposed. The two fingers are tendon actuated and employ two types of bistable mechanisms for quick response and linkage bending. The geometric relationship between the thumb and length of the hyperelastic rings was analyzed in the bending process, from which a potential energy model was established. A high-speed camera was used to capture the movement of the gripper, and it indicated that the grasping process time was less than 0.2 s. Moreover, the gripper can grasp various objects, including fragile and irregularly shaped items. Consequently, the current soft gripper can integrate speed, safety, and compliance through simple mechanical designs.

Sensorized Reconfigurable Soft Robotic Gripper System for Automated Food Handling

This article presents a versatile soft robotic gripper system whereby its fingers can be reconfigured into different poses such as scoop, pinch, and claw. This allows the gripper to efficiently and safely handle food samples of different shapes, sizes and stiffness such as uncooked tofu and broccoli floret. The 3D-printed fingers were tested to last up to 25 000 cycles without significant changes in the curvature profile and force output profile. A benchmark experiment was conducted to evaluate the performance of the gripper and state-of-the-art gripping solutions. Capability of versatile soft gripper was optimized by integrating vision and tactile sensing facilities. An object recognition system was developed to identify food samples such as potato, broccoli, and sausage. Position and orientation of food samples were identified and pick-and-place pathway was optimized to achieve the best gripping performance. Flexible tactile sensors were integrated into soft fingers and closed-loop force feedback control system was developed. This allowed the gripper to automatically explore and select the most stable grip pose for different food samples. Integration of vision and force feedback system ensure that objects detected by the system would be firmly gripped. The reconfigurable soft robotic gripper system has been demonstrated to perform high-speed pick-and-place tasks (∼3 s per item) with object recognition system, making it a potential solution to food and grocery supply chain needs.

Adaptive reversible composite-based shape memory alloy soft actuators

This research demonstrates how a combination of two-way shape memory alloy (SMA), low-temperature liquid epoxy cure composites, and fibre reinforced plastic (FRP) may be utilised to create a novel reversible actuator with built driven functionality. The novelty of this work is that the actuator can reverse its original shape and be mounted on different customized structures. The strategy is based on a knowledge of SMA wires and the manufacturing principle underlying composite structure, as well as experiments to see how soft SMA-FRP can be programmed to bend. The folding mechanism is studied in terms of fabrication factors such as SMA training and strong interfacial bonding between SMA and epoxy resin, which influence the programming process and shape change. The two-way SMA wires are trained using the pre-straining method to programme the SMAs. The technique has been used to assemble the SMA wires with bond reliability to enhance the actuator interface's thermal behaviour. The SMA elements are directly inserted into FRP strips and epoxy resin is used as an adhesive, resulting in dynamic hybrid composites. The module is actuated using an electrical board with a current value between 3 and 6 A. The robustness, controllability, mechanical properties, and 500 life cycles of the actuator are tested. Results indicate a bending angle of 58° with 30 mm of deflection in 7 s after actuating the module. Also, 3D printing is used to print a gripper inspired by human fingers and a structure to lift various weights. The actuator’s performance as a soft gripper is reliable in terms of grasping objects of different shapes. • Fabricating a novel fast responsive composite-based shape memory alloy actuator. • Developing reversible SMA-FRP soft actuators which can be mounted on various designs. • Adjusting current intensity and FRP/epoxy resin thickness, soft actuators demonstrated electrically reversible bending. • Programming of two-way shape memory alloy wires. • Grasping/release is achieved in an electrically-actuated gripper by 3D-printed structures.

Resonant Pneumatic Tactile Sensing for Soft Grippers

Soft robots capable of dexterous manipulation can enable the exploration of extreme environments. Equipping these robots with tactile sensing is a challenge, as sensors must be flexible, stretchable, and robust to environmental conditions. We present a tactile sensor design with a pneumatically driven acoustic resonator, without electronics near from the end-effector. For applications to soft grippers, we measure the resonant frequency of a soft tube undergoing stretching and bending. A small hole along the resonant tube enables contact sensing and pretouch up to 2 mm away. We also measure resonant frequency for a rigid uni-axial force sensing probe. Grasping tasks utilize three sensing modalities of a soft gripper; finger pose, fingertip contact, and force in the palm all provide feedback for dexterous manipulation. We discuss and address in future work the effects of atmosphere and air flow rate on resonant frequency as well as limitations in signal processing of this sensor design.

Semantic Grasping Via a Knowledge Graph of Robotic Manipulation: A Graph Representation Learning Approach

Semantic grasping aims to make stable robotic grasps suitable for specific object manipulation tasks. While existing semantic grasping models focus only on the grasping regions of objects based on their affordances, reasoning about which gripper to use for grasping, e.g., a rigid parallel-jaw gripper or a soft gripper, and how strongly to grasp the target object allows more sophisticated robotic manipulation. In this letter, we create a knowledge graph of robotic manipulation named roboKG to represent information about objects (e.g., the material and the components of an object), tasks, and appropriate robotic manipulation such as which component of an object to grasp, which gripper to use, and how strongly to grasp. Using knowledge graph embedding, we generate semantic representations of the entities and relations in roboKG, enabling us to make predictions on robotic manipulation. Based on the predicted gripper type, grasping component, and grasping force, a real robot performs seven different real-world tasks on 42 household objects, achieving an accuracy of 95.21%.

Self-Deformable Flexible MEMS Tweezer Composed of Poly(Vinylidene Fluoride)/Ionic Liquid Gel for Electrical Measurements and Soft Gripping

We present a self-deformable flexible tweezer capable of simultaneous mechanical handling and electrical measurements. The tweezer has a soft cantilever with the dimensions 2 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times8$ </tex-math></inline-formula> mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 75- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100~\mu \text{m}$ </tex-math></inline-formula> , and undergoes self-deformation. The device is shown to be successfully capable of detecting electrical signals by gently touching the surface and grasping a spherical bead. The device demonstrated the lowest working voltage (1.5 VDC), force suitable for soft gripping, and curvature radius of 2 mm, that was one of the smallest values compared to that of similar state-of-the-art devices. The device was fabricated using a unique and highly reliable process that was specifically developed to produce flexible cantilevers with novel ionic polymer-metal composites (IPMCs). The materials used were poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE) and an ionic liquid (IL). The PVDF-TrFE/IL gel was prepared using acetone as the solvent and the gel was coated with silver nanowires as the electrodes. The actuator with a length of 8 mm and containing 50 wt% IL yielded the largest bending displacement of 7 mm and minimum curvature radius of 2 mm at 1.5 VDC. [2022-0026]

Automated Design of Embedded Constraints for Soft Hands Enabling New Grasp Strategies

Soft robotic hands allow to fully exploit hand-object-environment interactions to complete grasping tasks. However, their usability can still be limited in some scenarios (e.g., restricted or cluttered spaces). In this article, we propose to enhance the versatility of soft grippers by adding special passive components to their structure, without completely altering their design, nor their control. A method for the automated design of soft-rigid scoop-shaped add-ons acting as “embedded constraints” is presented. Given a certain gripper and a large set of objects, the design parameters of the optimal scoop for each object are derived by solving an optimization problem. Also the object-environment relative pose is considered in the optimization. The obtained “optimal scoops” are clustered to get a limited set of representative scoop designs which can be prototyped and used in grasping tasks. In this article, we also introduce a data-driven method allowing a grasp planner to select the most suitable scoop to be added to the used hand, given a certain object and its configuration with respect to the surrounding environment. Experiments with two different hands validate the proposed approach.

Optimizing Out-of-Plane Stiffness for Soft Grippers

In this letter, we presented a data-driven framework to optimize the out-of-plane stiffness for soft grippers to achieve mechanical properties as hard-to-twist and easy-to-bend. The effectiveness of this method is demonstrated in the design of a soft pneumatic bending actuator (SPBA). First, a new objective function is defined to quantitatively evaluate the out-of-plane stiffness as well as the bending performance. Then, sensitivity analysis is conducted on the parametric model of an SPBA design to determine the optimized design parameters with the help of Finite Element Analysis (FEA). To enable the computation of numerical optimization, a data-driven approach is employed to learn a cost function that directly represents the out-of-plane stiffness as a differentiable function of the design variables. A gradient-based method is used to maximize the out-of-plane stiffness of the SPBA while ensuring specific bending performance. The effectiveness of our method has been demonstrated in physical experiments taken on 3D-printed grippers.