Soft Pneumatic Gripper Research Articles

An effective nonlinear dynamic formulation to analyze grasping capability of soft pneumatic robotic gripper

ABSTRACT Soft pneumatic robotic grippers have found extensive applications across various engineering domains, which prompts active research due to their splendid compliance, high flexibility, and safe human-robot interaction over conventional stiff counterparts. Previously simplified rod-based models principally focused on clarifying overall large deformation and bending postures of soft grippers from static or quasi-static perspectives, whereas it is challenging to elaborate grasping characteristics of soft grippers without considering contact interaction and nonlinear large deformation behaviors. To address this, based on absolute nodal coordinate formulation (ANCF), comprehensively allowing for structural complexity, geometric, material and boundary nonlinearities, and incorporating Coulomb’ friction law with a multiple-point contact method, we put forward an effective nonlinear dynamic modeling approach for exploring grasping capability of soft gripper. Moreover, we solved the established dynamic equations using Generalized-α scheme, and conducted thorough numerical simulation analysis on a three-jaw soft pneumatic gripper (SPG) in terms of grasping configurations, displacements and contact forces. The proposed dynamic approach can accurately both describe complicated deformed configurations along with stress distribution and provide a feasible solution to simulate grasping targets, whose effectiveness and precision were analyzed theoretically and verified experimentally, which may shed new light on devising and optimizing other multifunctional SPGs.

Design and development of a variable structure gripper with electroadhesion

Soft grippers are a novel kind of front-end actuators for robotics that offer great benefits such as easy control, superior grabbing capability, and close contact with the environment. They have vast application possibilities in numerous industries such as agricultural picking, item sorting, and medical rehabilitation. In this paper, a soft gripper with a variable structure and electrostatic adsorption is proposed. The gripper includes three fingers uniformly dispersed in the shape of a circle, which can adapt to varying sizes of grabbing objects by dynamically modifying the opening angle of the fingers. Aimed at addressing the existing issue of lacking multi fingers soft pneumatic grippers (SPGs) in grabbing tiny flat items, it is enhanced by embedding an electroadhesion (EA) films at the bottom of the soft pneumatic fingers of the gripper. It is simulated that the diameter adjustment range of this gripper is 0–482 mm, and the angle adjustment range is 0–180° via ABAQUS simulation. Finally, the adaptive grabbing capacity of the soft gripper was validated via experiments. The trials reveal that the gripper can grab items of different sizes by altering the opening angle of the fingers and the maximum load of the gripper can reach 10.91 N during specific grasping operations. The findings confirm that the SPGs with variable structure and EA described in this paper has a high gripping range and the capacity to grab thin flat items. We believe that its excellent gripping performance will encourage different uses of this gripper in everyday life and industry.

Design and manufacturing process of pneumatic soft gripper for additive manufacturing

The soft gripper, constructed from elastic materials, serves as a crucial automated device component, aiming to minimize object damage. The central focus of utilizing soft grippers lies in their shape design, enabling effective handling of objects with low rigidity and diverse forms. This study delves into shape design research, employing a pneumatic pressure-responsive, tube-like soft gripper fabricated through injection molding. During the design phase, a comprehensive survey of soft gripper research trends was conducted, leading to two distinct configurations: Type1, drawing from established shapes, and Type2, a novel design ensuring bending angle stability. The primary dimensions of Soft Gripper Type 1 and Type 2 are as follows: lengths of 78.11 mm and 74.96 mm, heights of 18.69 mm and 20.0 mm, respectively, with a uniform thickness of 0.6 mm. The prediction of bending angles was accomplished through employment of the Abaqus finite element analysis program. In both simulation and experimentation, pneumatic pressures of 100, 200, and 300 kPa were applied to compare the bending angles of two types of soft grippers. While conventional injection molding remains a prevalent manufacturing technique, it confronts challenges like demolding and undercuts. Thus, for intricate shapes and monolithic soft grippers, layer-by-layer additive manufacturing emerges as a superior choice over injection molding. The implementation of this approach holds the potential for streamlined soft gripper design processes, potentially yielding reductions in both time and cost. The significance of these findings lies in advancing the capabilities of soft grippers, propelling them toward efficient and cost-effective applications in various fields.

The Enhanced Adaptive Grasping of a Soft Robotic Gripper Using Rigid Supports

Soft pneumatic grippers can grasp soft or irregularly shaped objects, indicating potential applications in industry, agriculture, and healthcare. However, soft grippers rarely carry heavy and dense objects due to the intrinsic low modulus of soft materials in nature. This paper designed a soft robotic gripper with rigid supports to enhance lifting force by 150 ± 20% in comparison with that of the same gripper without supports, which successfully lifted a metallic wrench (672 g). The soft gripper also achieves excellent adaptivity for irregularly shaped objects. The design, fabrication, and performance of soft grippers with rigid supports are discussed in this paper.

Adaptive pneumatic soft gripper with embedded flexible bending sensor

Purpose The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects. Design/methodology/approach Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted. Findings In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested. Originality/value Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

Optimizing surface roughness in soft pneumatic gripper fabricated via FDM: experimental investigation using Taguchi method

Purpose In this study, experimental studies were carried out using different process parameters of the soft pneumatic gripper (SPG) fabricated by the fused deposition modeling method. In the experimental studies, the surface quality of the gripper was examined by determining four different levels and factors. The experiment was designed to estimate the surface roughness of the SPG.Design/methodology/approach The methodology consists of an experimental phase in which the SPG is fabricated and the surface roughness is measured. Thermoplastic polyurethane (TPU) flex filament material was used in the fabrication of SPG. The control factors used in the Taguchi L16 vertical array experimental design and their level values were determined. Analysis of variance (ANOVA) was performed to observe the effect of printing parameters on the surface quality. Finally, regression analysis was applied to mathematically model the surface roughness values obtained from the experimental measurements.Findings Based on the Taguchi signal-to-noise ratio and ANOVA, layer height is the most influential parameter for surface roughness. The best surface quality value was obtained with a surface roughness value of 18.752 µm using the combination of 100 µm layer height, 2 mm wall thickness, 200 °C nozzle temperature and 120 mm/s printing speed. The developed model predicted the surface roughness of SPG with 95% confidence intervals.Originality/value It is essential to examine the surface quality of parts fabricated in additive manufacturing using different variables. In the literature, surface roughness has been examined using different factors and levels. However, the surface roughness of a soft gripper fabricated with TPU material has not been examined previously. The surface quality of parts fabricated using flexible materials is very important.

SynapNet: A Complementary Learning System Inspired Algorithm With Real-Time Application in Multimodal Perception.

Catastrophic forgetting is a phenomenon in which a neural network, upon learning a new task, struggles to maintain its performance on previously learned tasks. It is a common challenge in the realm of continual learning (CL) through neural networks. The mammalian brain addresses catastrophic forgetting by consolidating memories in different parts of the brain, involving the hippocampus and the neocortex. Taking inspiration from this brain strategy, we present a CL framework that combines a plastic model simulating the fast learning capabilities of the hippocampus and a stable model representing the slow consolidation nature of the neocortex. To supplement this, we introduce a variational autoencoder (VAE)-based pseudo memory for rehearsal purposes. In addition by applying lateral inhibition masks on the gradients of the convolutional layer, we aim at damping the activity of adjacent neurons and introduce a sleep phase to reorganize the learned representations. Empirical evaluation demonstrates the positive impact of such additions on the performance of our proposed framework; we evaluate the proposed model on several class-incremental and domain-incremental datasets and compare it with the standard benchmark algorithms, showing significant improvements. With the aim to showcase practical applicability, we implement the algorithm in a physical environment for object classification using a soft pneumatic gripper. The algorithm learns new classes incrementally in real time and also exhibits significant backward knowledge transfer (KT).

A versatile and high-load soft gripper enabled by vacuum-assisted bio-inspired interfacial adhesion

Abstract Soft robotic grippers have gained considerable attention owing to their highly compliant, adaptive, and safe characteristics in a large variety of scenes, especially involving human-machine interactions. However, the low-stiffness nature of the soft material and the multi-finger gripping mechanism make soft grasping systems suffer in applications requiring relatively high load capacity and broad grasping adaptability. Despite extensive efforts to develop soft grippers with tunable stiffness by constructing smart materials and structures, the resultant load capacity is often compromised by sacrificing working efficiency or surface adaptability. In this work, we report a paradigm to design a versatile, high-load (>2 kg), and fast-response (<1 s) pneumatic soft gripper by strengthening the contact interface via bio-inspired controllable adhesion. A mushroom-shaped micropatterned dry adhesive surface is integrated with a soft pneumatic bidirectionally bendable actuator via a vacuum-assisted equal load-sharing design. This gripper extends the adaptable object diameter from 15 mm to infinity and significantly increases the load capacity to over 2 kg without compromising the original compliance. The multifunctional grasping modes and high load capacity are successfully demonstrated by grasping objects with diverse material components, various surface shapes.

Design and fabrication of multi-material pneumatic soft gripper using newly developed high-speed multi-material vat photopolymerization 3D printer

Design and fabrication of multi-material pneumatic soft gripper using newly developed high-speed multi-material vat photopolymerization 3D printer

A stretchable all-nanofiber iontronic pressure sensor

Flexible pressure sensors with high stretchability, sensitivity, and stability are undoubtedly urgently required for potential applications in intelligent soft robots, human-machine interaction, health monitoring, and other fields. However, most current flexible pressure sensors are unable to endure large deformation and are prone to performance degradation or even failure during frequent operation due to their multilayered structures. Here, we propose a stretchable all-nanofiber iontronic pressure sensor that is composed of ionic nanofiber membranes used as dielectric layers and liquid metal used as electrodes. This sensor exhibits a high sensitivity of 1.08 kPa-1 over a wide range of 0-300 kPa, with a fast response-relaxation time of about 18/22 ms and excellent stability. The high sensitivity comes from the electric double layer formed at the ionic film/electrode interface, while high stretchability and stability are enabled by in-situ encapsulated all-nanofiber structures. As a proof of concept, a prototype sensor array is integrated into a soft pneumatic gripper, demonstrating its capability of pressure perception and object recognition during the grasping process. Thus, the scheme provides another excellent strategy to fabricate stretchable pressure sensors with superb performance in terms of high stretchability, sensitivity, and stability.

Grasping Profile Control of a Soft Pneumatic Robotic Gripper for Delicate Gripping

Soft pneumatic grippers (SPGs) have garnered significant attention and recognition in various industries owing to their remarkable flexibility, safety, and adaptability. They excel in manipulating delicate, irregularly shaped, and soft objects, surpassing the limitations of conventional grippers. However, effective control techniques for managing the grasping profile of SPGs are still under development. Simple on–off pressure control using a regulator valve is inadequate for delicate gripping with pneumatic robot grippers. To address this, a synergy pressure control system was implemented. In addition, a proportional–integral–derivative control technique, complemented by an unknown input observer, was devised to control the volume of the soft pneumatic robotic gripper, ensuring its alignment with the desired volume level. The simulation and experimental results provide substantial evidence of the effectiveness of the developed control technique and the unknown input observer in managing the volume and pressure of the gripper. Consequently, this breakthrough empowers precise and delicate gripping actions, enabling the handling of delicate objects such as tofu.

Research on a Variable Pressure Driving Method for Soft Robots Based on the Electromagnetic Effect.

This study proposes a novel variable air pressure supply structure based on the electromagnetic effect. This structure can be implemented in various soft robots driven by air pressure, including pneumatic artificial muscles, pneumatic soft grippers, and other soft robots. The structure's main body comprises a hollow circular tube, a magnetic piston arranged in the tube, and an electromagnetic solenoid nested outside the tube. The electromagnetic solenoid is designed with special winding and power supply access modes, generating either an attractive force or a repulsive force on the magnetic piston. This solenoid conforms with the magnetic piston expectation in the tube by changing the polarity direction. The interior of the whole structure is a closed space. The gas is conveyed to the soft robot by the gas guide hoses at the two ends of the structure, and the expansion energy of the compressed gas is fully utilized. Then, the gas supply pressure is controlled to drive the robot. The mathematical model of the structure is established based on the analysis of the electromagnetic force and gas pressure on the piston. The simulation results show that the structure's inherent vibration characteristics under various parameters align with expectations. The real-time automatic optimization of the controller parameters is realized by optimizing the incremental proportional-integral-derivative (PID) controller based on a neural network. The simulation results show that the structure can meet the application requirements. The experimental results show that the proposed gas supply structure can provide a continuous pressure supply curve with any frequency in a specific amplitude range and has an excellent tracking effect on the sinusoidal-like pressure curve.

Transporting Dispersed Cylindrical Granules: An Intelligent Strategy Inspired by an Elephant Trunk

Manipulating granular materials is a crucial function of robotic grippers. However, the existing approaches always suffer from low efficiency when dealing with large quantities of dispersed granules. To overcome this challenge, inspiration is drawn from an African elephant (Loxodonta Africana), which can employ both fingertip extensions on the trunk tip to efficiently grasp dispersed granular food all at once by mediating state transition of granules. Herein, this bio‐inspired intelligent strategy is integrated into a soft pneumatic gripper for transporting dispersed granules. To evaluate the critical actuation pressures while grasping granules, a library is constructed experimentally, and the effects of the initial relative height and relative lifting speed on the grasping success rate are examined. It is indicated in the experimental results that this trunk‐inspired robotic strategy leads to a success rate of over 90% and saves ≈50% duration of manipulation compared to the individual gripping fashion. Herein, new insights may be offered in this study into a novel manipulation strategy for efficiently transporting dispersed granular materials.

Advanced Stiffness Sensing through the Pincer Grasping of Soft Pneumatic Grippers.

In this study, a comprehensive approach for sensing object stiffness through the pincer grasping of soft pneumatic grippers (SPGs) is presented. This study was inspired by the haptic sensing of human hands that allows us to perceive object properties through grasping. Many researchers have tried to imitate this capability in robotic grippers. The association between gripper performance and object reaction must be determined for this purpose. However, soft pneumatic actuators (SPA), the main components of SPGs, are extremely compliant. SPA compliance makes the determination of the association challenging. Methodologically, the connection between the behaviors of grasped objects and those of SPAs was clarified. A new concept of SPA modeling was then introduced. A method for stiffness sensing through SPG pincer grasping was developed based on this connection, and demonstrated on four samples. This method was validated through compression testing on the same samples. The results indicate that the proposed method yielded similar stiffness trends with slight deviations in compression testing. A main limitation in this study was the occlusion effect, which leads to dramatic deviations when grasped objects greatly deform. This is the first study to enable stiffness sensing and SPG grasping to be carried out in the same attempt. This study makes a major contribution to research on soft robotics by progressing the role of sensing for SPG grasping and object classification by offering an efficient method for acquiring another effective class of classification input. Ultimately, the proposed framework shows promise for future applications in inspecting and classifying visually indistinguishable objects.

Fabric‐Based Star Soft Robotic Gripper

Soft pneumatic gripping strategies are often based on pressurized actuation of structures made of soft elastomeric materials, which limits designs in terms of size, weight, achievable forces, and ease of fabrication. In contrast, fabric‐based inflatable structures offer high stiffness‐to‐weight ratio solutions for soft robotics, but their actuation has been little explored. Herein, a new class of pneumatic soft grippers is presented that exploits the in‐plane overcurvature effect of inextensible fabric flat balloons upon inflation. A star‐shaped gripper contracts radially under pressure producing a gripping force on the object whose intensity can be modulated by the pressure input. First, the kinematics and mechanics of a single V‐shaped actuator are studied through experiments, finite element simulations, and analytical models. Then, these results are leveraged to predict the mechanical response of the entire star, optimize its geometry, and maximize contraction and stiffness. It is shown that the gripping performance can be improved by stacking several stars with silicon‐coated corners. It is expected that the flexibility, robustness, scalability, and ease of fabrication of this methodology will lead to a new generation of lighter and larger actuators capable of developing higher forces and moving delicate and irregularly shaped objects while maintaining reasonable complexity.

Design of squeezing-tube-driven pump for soft pneumatic robotics based on spiral spring winding

Aiming at the demand for high-speed, easy-controllability, and integration of pneumatic soft robots and elastomer actuators, this study presents a squeezing-tube-driven pump (STDP) for soft pneumatic robotics based on spiral spring winding. This concept contains a customized spiral spring and a pneumatic tube with high-elasticity. The spiral spring is driven by an electric motor and coerced into winding deformation. Furthermore, the pneumatic tube is extruded by the spring and then the air in the tube is fast compressed to drive soft pneumatic grippers. The mechanical model and simulation are utilized to explain the operating principle of STDP. The air pressure and rotation angle of the spring under various rotation speeds are in a close linear correlation verified by the experimental results, which provides feasibility for easy controlling and rapid actuation. Finally, fast-gripping tests with an integrated gripper–pump system and a pneumatic muscle actuation test are presented to show the advantages of the proposed pump, respectively.

Reconfigurable bionic soft pneumatic gripper for fruit handling based on shape and size adaptation

A universal soft gripper for fruit grasping is challenging to develop. In this study, a modular and reconfigurable soft pneumatic gripper was designed. The designed gripper was inspired by the dexterous grasping of the human hand for fruits of different shapes and sizes. It comprised three soft extension actuators (SEAs), two soft rotation actuators (SRAs), and three soft bending actuators (SBAs). By adjusting SRAs, two grasping poses (claw and clenching pose) could be made to hold fruits of different shapes. The grasping size under each pose could be continuously adjusted by SEAs to grasp fruits of different sizes. SBAs were used to mimic soft fingers for grasping. Theoretical and simulation models were established to predict the relationships between deformations and pressures of SEAs, SRAs, and SBAs. The deformation characteristics of these actuators were experimentally investigated. It was shown that, by inflating SEAs, the grasping sizes under the claw and clenching poses could be increased by 87.5% and 94.5%, respectively. Furthermore, a visual recognition system was designed for automatically controlling the grasping pose and size. Grasping tests showed that, by reconfiguring the grasping pose and size, various fruits, vegetables, and foods with weights from 32 to 786 g (24.6 folds) and diameters from 30 to 141 mm (4.7 folds) could be successfully grasped, indicating the broad applicability of our all-pneumatic soft gripper.

Adaptive Pincer Grasping of Soft Pneumatic Grippers Based on Object Stiffness for Modellable and Controllable Grasping Quality

In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The grasping kinetics was analyzed. The connection between grasping quality and SPA performance is discussed. We also devised a subjective definition of grasping quality due to SPA performance. A modeling technique was established, which makes dominant factors of grasping quality due to the SPA performance predictable over the gripper input. Later, a control architecture was developed. This architecture demonstrates how the grasping is implemented. The modeling technique was used to forecast grasping quality due to the SPA performance and its factors. An experiment was conducted to obtain actual results. The predicted and actual results were correspondingly compared. The results show minute deviation, thereby validating the reliability of the grasping. This study clarifies the association between grasping quality and SPA performance and contributes an advancement toward modellable and controllable task-level variables, such as grasping quality, in SPG pincer grasping.

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.

A Soft Pneumatic Gripper with Endoskeletons Resisting Out-of-Plane Bending

The established soft pneumatic grippers have the benefit of flexible and compliant gripping, but they cannot withstand lateral loads, due to the low stiffness of soft material. This paper proposes an endoskeleton gripper. The soft action of the finger is performed by air chambers, and the gripping force is transferred by the rigid endoskeleton within the finger. The endoskeleton in the finger is similar to a wristwatch chain; the hinge mechanism permits relative rotation in the working plane but restricts out-of-plane bending, greatly increasing the finger stiffness. The endoskeleton and gripper holder can be 3D-printed with CR-PLA material. The finger was fabricated by molding of silicone gel. The gripper can perform enveloping grasping and pinch grasping operations depending on the object size, weight, and surrounding environment. The finger bending and gripper grasping performance were investigated by experiments and finite element analysis. The fingertip force of the endoskeleton gripper was about 1.45 times higher than that of the gripper without endoskeleton. It was found that the gripper can grasp objects with a maximum diameter of 80.5 mm and a weight of 450 g, which were 80.5% of the finger length and six times the finger self-weight, respectively.