Soft Gripper Research Articles

Deformation Modeling and Simulation of a Novel Bionic Software Robotics Gripping Terminal Driven by Negative Pressure Based on Classical Differential Algorithm.

A general pneumatic soft gripper is proposed in this paper. Combined with the torque balance theory, the mathematical theoretical model of bending deformation of soft gripper is established based on Yeoh constitutive model and classical differential geometry. Assuming that the pressure in each inner cavity is evenly distributed, the input gas is in an ideal state, which is approximately treated as an isothermal condition, and all orifices experience blocked flow. In addition, compared with the mechanical work of gas, the energy related to gas flow and heat transfer is negligible. The nonlinear mechanical properties of silicone rubber are studied. It is regarded as isotropic and incompressible material, which is characterized by strain energy per unit volume. The material constant coefficients C10 and C20 are determined through the uniaxial tensile test, and the software gripper is simulated on the ABAQUS platform. The bending deformation models of grippers with three different force-bearing cavity structures are analyzed and compared, and the software clamping structure with the bending deformation most in line with the application conditions is selected. The limit input air pressure of the gripper and the situation of enveloping the clamping target object are analyzed. Through the bending deformation experiment, the maximum deformation angle is 72.4°. The relative error between the simulation analysis data and the prediction results of the mathematical model is no more than 3.5%, which verifies the effectiveness of the simulation and the correctness of the mathematical theoretical model of bending deformation. The soft manipulator proposed in this paper has good adaptability to grasping objects of different shapes and sizes. The minimum diameter of the target object that can be clamped is 0.1 mm. It can clamp the object weighing up to 1 kg. It has compact size, light weight, high ductility, and flexibility.

A soft gripper with contamination resistance and large friction coefficient

With the development of soft gripper systems, food processing, packaging, and processing technology has seen a significant advancement. The soft gripper must be protected from surface contamination and liquid lubrication; hence, a hydrophobic and contamination-resistant surface is used. There is an urgent need for a soft gripper that meets the functions of hydrophobic performance and contamination resistance, but there has been little study. In this study, the two functions are well achieved by introducing a flexible superhydrophobic surface. A novel design of a flexible superhydrophobic surface-based gripper (SSBG) is proposed by the template method. After a series of testing, it was discovered that the friction coefficient between the SSBG surface and the glass plate, cardboard, and steel plate is larger than that of a standard surface gripper (SSG). At the same time, the contamination resistance of SSBG is particularly important. Because of the existence of the plastron layer, the surface was discovered to be able to repel bacterial colonization. Finally, when the usual gripping force of the SSBG is measured on a 250 ml beaker with contamination and liquid lubrication, it can be shown that the gripping ability is improved by at least 100% and 170% compared to the SSG, respectively. As a result, the SSBG has a high potential for utilization in industrial and therapeutic contexts.

Self-healing sensorized soft robots

The lifetime of soft robots is limited by their susceptibility to damage. Recent breakthroughs in healable soft robots have overcome this issue by manufacturing systems from self-healing polymers. However, to operate and recover autonomously, compatible sensors need to be embedded. We show that innovative healable soft sensors to measure strain, force, and damage, based on a self-healing conductive elastomeric composite, were developed and integrated with near-perfect interfacial strength in a healable soft gripper. The paper details the complete development of the gripper, including the selection of the conductive composite based on carbon black and nanoclay, sensor and actuator characterization, and its manufacturing. The gripper with embedded sensors recovers its actuation, sensor function, and damage detection after being severely damaged, and this multiple times.

Frictional shear stress of ZnO nanowires on natural and pyrolytic graphite substrates

The friction behaviour of ZnO nanowires on natural graphite (NG) and highly oriented pyrolytic graphite (HOPG) substrates was tested in ambient conditions by use of optical microscopy based nanomanipulation. Nanowires on the step-free and waviness-free NG substrate exhibit a diameter-independent nominal frictional shear stress of 0.48 MPa, and this provides a benchmark for studying how the surface topography of graphite influences nanowire friction. Nanowires on the HOPG substrate present a significant diameter-dependent frictional shear stress, increasing from 0.25 to 2.78 MPa with the decrease of nanowire diameter from 485 to 142 nm. The waviness of HOPG has a limited effect on the nanowire friction, as a nanowire can fully conform to the substrate. The surface steps on the HOPG can significantly enhance the nanowire friction and lead to a much higher frictional shear stress than that on NG due to mechanical blocking and the presence of a Schwoebel barrier at step edges. The surface steps, however, can also generate small wedge-shaped gaps between a nanowire and substrate, and thus reduce the nanowire friction. With the decrease in nanowire diameter, the capacity for the nanowire to better conform to the substrate reduces the length of the wedge-shaped gaps, leading to the observed increase in nanowire friction. The results have improved our understanding of the unique friction behaviour of nanowires. Such an improved understanding is expected to benefit the design and operation of nanowire-friction-based devices, including bio-inspired fibrillar adhesives, soft grippers, rotary nanomotors, and triboelectric nanogenerators.

A High Performance Pneumatically Actuated Soft Gripper Based on Layer Jamming

Abstract This article presents a novel soft robotic gripper with a high payload capacity based on the layer jamming technology. Soft robots have a high adaptability, however suffer a low payload capacity. To overcome these conflicting challenges, here we introduce a 3D printed multi-material gripper that integrates jamming layers for enhancing payload capacity. By inflating the internal air chamber with positive pressure, the finger can be actuated to a large bending angle for adapting complex shapes. Layers of jamming sheets are bounded on the finger structure and are then sealed inside a vacuum bag. When a high payload is desired, air inside the vacuum bag is drawn out and a negative air pressure is applied to the jamming layers, which leads to the gripper locked at the actuated shape. To evaluate the performance of the gripper, we conducted extensive tests including actuation, stiffness variation, typical payload capacity, and adaptability. The results show that our gripper is not only highly adaptable just like most soft grippers but also more importantly capable of grasping heavy (about 6–10 kg) objects comparable to rigid-body counterparts.

A Soft and Bistable Gripper with Adjustable Energy Barrier for Fast Capture in Space.

Actuators for fast capture are essential in the tasks of space structure assembly and space debris disposal. To avoid damage and rebound caused by collision, the mechanical devices for capture or docking impose very strict restrictions on the collision speed. The gripper made of soft material can realize compliant grasping, but its actuating speed and driving mode should adapt to the scenarios of grasping moving objects in space. By harnessing the rapid occurrence of structural instability and tuning its triggering conditions, we present a soft and bistable gripper for dynamic capture. The gripper deforms on the collision with other objects, and it absorbs the kinetic energy of the objects to trigger an instability, and then achieve fast grasping as well as cushioning. This process does not need any other input energy, and it greatly simplifies the conventional driving devices so as to realize the miniaturized and light-weight gripping actuation. The proper pre-deformation to the bistable structure of the gripper enables one to dynamically adjust the energy barrier for triggering the onset of instability to achieve the optimal grasping and buffering effect according to the kinetic characteristics of targets. After finishing one grasping task, the bistable gripper can automatically return to its initial state and release the target via a self-designed cable-driven mechanism. The ground-testing experiment demonstrates that the proposed soft gripper is capable to grasp, transfer, and release moving targets, and it thus possesses great potential to fulfill challenging operations in space missions.

Humins Blending in Thermoreversible Diels-Alder Networks for Stiffness Tuning and Enhanced Healing Performance for Soft Robotics.

Humins waste valorization is considered to be an essential pathway to improve the economic viability of many biorefinery processes and further promote their circularity by avoiding waste formation. In this research, the incorporation of humins in a Diels–Alder (DA) polymer network based on furan-maleimide thermoreversible crosslinks was studied. A considerable enhancement of the healing efficiency was observed by just healing for 1 h at 60 °C at the expense of a reduction of the material mechanical properties, while the unfilled material showed no healing under the same conditions. Nevertheless, the thermal healing step favored the irreversible humins polycondensation, thus strengthening the material while keeping the enhanced healing performance. Our hypothesis states a synergistic healing mechanism based on humins flowing throughout the damage, followed by thermal humins crosslinking during the healing trigger, together with DA thermoreversible bonds recombination. A multi-material soft robotic gripper was manufactured out of the proposed material, showing not only improved recovery of the functional performance upon healing but also stiffness-tunable features by means of humins thermal crosslinking. For the first time, both damage healing and zone reinforcement for further damage prevention are achieved in a single intrinsic self-healing system.

Laser-Sculptured Hierarchical Spinous Structures for Ultra-High-Sensitivity Iontronic Sensors with a Broad Operation Range.

Tactile pressure sensing over a wide operation range (>1 MPa) is challenging for a variety of applications in fields such as aviation, oceanography, and biomedicine. Recently, innovative strategies have been utilized to improve the performances of tactile sensors using specially designed structures, dielectric layers, and electrodes. Here, a hierarchical structural design based on ionic gel films has been utilized to build iontronic pressure sensors with ultrahigh sensitivities and broad operation ranges. Sculptured patterns made by a controlled CO2 laser scanning process have been produced on polyimide films to achieve two kinds of protrusion structures for high specific surface areas and strength to withstand high pressure. The iontronic sensor has been constructed by adding two screen-printed electrodes of high surface areas to achieve an ultrahigh sensitivity of 2593 kPa-1 and a wide pressure range from 0 Pa to 3.36 MPa. The prototype device also has a fast response and recovery time of 26 and 13 ms, respectively, and an excellent mechanical durability in the endurance test of over 2700 repeated loading and unloading cycles under a pressure of 1 MPa. Several application examples have been demonstrated, including the detection of physiological signals on human volunteers, the feedback control of intelligent robots, the grasping operation of underwater soft grippers, and the environmental wind-speed monitoring. As such, this work demonstrates a versatile and economical methodology to produce high-performance flexible sensors for various potential applications.

An AI-Assisted and Self-Powered Smart Robotic Gripper Based on Eco-EGaIn Nanocomposite for Pick-and-Place Operation.

High compliance and muscle-alike soft robotic grippers have shown promising performance in addressing the challenges in traditional rigid grippers. Nevertheless, a lack of control feedback (gasping speed and contact force) in a grasping operation can result in undetectable slipping and false positioning. In this study, a pneumatically driven and self-powered soft robotic gripper that can recognize the grabbed object is reported. We integrated pressure (P-TENG) and bend (B-TENG) triboelectric sensors into a soft robotic gripper to transduce the features of gripped objects in a pick-and-place operation. Both the P-TENG and B-TENG sensors are fabricated using a porous structure made of soft Ecoflex and Euthethic Gallium-Indium nanocomposite (Eco-EGaIn). The output voltage of this porous setup has been improved by 63%, as compared to the non-porous structure. The developed soft gripper successfully recognizes three different objects, cylinder, cuboid, and pyramid prism, with a good accuracy of 91.67% and has shown its potential to be beneficial in the assembly lines, sorting, VR/AR application, and education training.

Glowing Sucker Octopus (Stauroteuthis syrtensis)-Inspired Soft Robotic Gripper for Underwater Self-Adaptive Grasping and Sensing.

A soft gripper inspired by the glowing sucker octopus (Stauroteuthis syrtensis)’ highly evolved grasping capability enabled by the umbrella‐shaped dorsal and ventral membrane between each arm is presented here, comprising of a 3D‐printed linkage mechanism used to actuate a modular mold silicone‐casting soft suction disc to deform. The soft gripper grasp can lift objects using the suction generated by the pump in the soft disc. Moreover, the protruded funnel‐shaped end of the deformed suctorial mouth can adapt to smooth and rough surfaces. Furthermore, when the gripper contacts the submerged target objects in a turbid environment, local suctorial mouth arrays on the suction disc are locked, causing the variable flow inside them, which can be detected as a tactile perception signal to the target objects instead of visual perception. Aided by the 3D‐printed linkage mechanism, the soft gripper can grasp objects of different shapes and dimensions, including flat objects, objects beyond the grasping range, irregular objects, scattered objects, and a moving turtle. The results report the soft gripper's versatility and demonstrate the vast application potentials of self‐adaptive grasping and sensing in various environments, including but are not limited to underwater, which is always a key challenge of grasping technology.

Design, Fabrication and Analysis of Magnetorheological Soft Gripper.

The magnetorheological elastomer is promising material for applications in soft robotics. Its properties like reactive to external magnetic field and softness allow to construct an attractive devices. This work presents a construction of soft gripper assembled with magnetorheological elastomers. The work describes the detailed molding process of magnetorheological elastomers. Further, the electromechanical properties of magnetorheological elastomers are shown using a simple beam. Finally, the soft gripper is constructed and analyzed with the series of experiments.

Combining Suction and Friction to Stabilize a Soft Gripper to Shear and Normal Forces, for Manipulation of Soft Objects in Wet Environments

Soft robotic gripping in wet environments is generally limited by the presence of a liquid that lubricates the interface between the gripper and an object being manipulated. The use of soft grippers is particularly beneficial for manipulating soft, delicate objects, yet is further limited by low grip strengths. We propose the use of suction, a form of adhesion that functions well in wet environments, to enhance soft robotic grippers. We stabilized the suction against shear disturbances using soft actuated fingers decorated with fluid-channeling patterns to enhance friction, counteracting the interfacial lubrication experienced in wet environments. We therefore combined the uses of attachment via suction and shear stability via friction to create an adhesive soft gripper. We evaluated the contributions to attachment of each component to help stabilize it against dislodgement forces that act in parallel and normal to an object that it aimed to manipulate. By identifying these contributions, we envision that such an adhesive gripper can be used to benefit soft robotic manipulation in a variety of wet environments, from surgical to subsea applications.

A 3D Printed Soft Robotic Gripper With a Variable Stiffness Enabled by a Novel Positive Pressure Layer Jamming Technology

In this research, a soft robotic gripper with a variable stiffness enabled by a novel positive pressure layer jamming technology was developed and fabricated in two materials using customized additive manufacturing. A novel positive layer jamming technology was developed for tuning stiffness of the gripper. Positive pressure layer jamming has a higher performance potential than conventional vacuum layer jamming since a higher pressure can be applied, approximately 1.6x higher in terms of payload capacity. Two different thermoplastics materials are printed together to form a relatively hard backbone and a relatively soft airtight actuation bellows. The implementation of positive layer jamming will be described, along with the additive manufacturing techniques used to produce the gripper and the test results of the final design. Experimental tests show that this soft gripper was able to vary its stiffness about 25x fold with the positive layer jamming. This work demonstrates that the positive pressure jamming offers a novel method for varying soft robot stiffness with higher payload capacity than the conventional vacuum based layer jamming technology.

Design of a Soft Gripper With Improved Microfluidic Tactile Sensors for Classification of Deformable Objects

Tactile object recognition is vital for robotic handling systems; however, existing technologies that concentrate on tactile sensors with high modulus are not suitable for soft grippers to classify deformable objects. In this letter, we integrated an indenter layer into the traditional microfluidic tactile sensor to increase its sensitivity based on the lensing effect of human skin. For the application of the developed sensor, we built HustGripper, a tendon-driven soft gripper, where the sensor was bonded on the fingertip. Experiments on the tactile classification of the deformable objects were conducted to validate the performance of the sensor, where different indenters, exploratory procedures, and data processing approaches were considered to explore the key factor to determine the classification accuracy.

A Bidirectional Soft Biomimetic Hand Driven by Water Hydraulic for Dexterous Underwater Grasping

Soft robotics shows considerable promise for various underwater applications. Soft grippers as end-effectors are particularly useful for compliant and robust grasping compared to rigid mechanisms. In this work, we describe the design, fabrication and operation of a soft robotic hand driven by water hydraulics for underwater grasping. The proposed design has, in addition to the five fingers of a human hand, an extra soft thumb arranged symmetrically in an active soft palm. The soft fingers are designed with four chambers to enable bidirectional bending and deflection motions. We propose a novel elastic fiber reinforced structure to enhance and constrain the flexion movements of three palm actuators. The versatility of the underwater robotic hand is evaluated by implementing the human grasping gestures of the Feix taxonomy. Furthermore, we present a low-cost one-camera-multiple-mirrors imaging approach for capturing the grasps from multiple viewpoints simultaneously.

Topology Optimization Design and Experiment of a Soft Pneumatic Bending Actuator for Grasping Applications

Soft pneumatic bending actuators are commonly used in robotic grasping applications and can be applied for handling both delicate and irregularlyshaped objects. Because these soft pneumatic actuators are typically embedded with multiple air chambers inside soft, thin structures, their maximum payloads are usually low compared to rigid designs of similar size. This article presents a soft pneumatic bending actuator design using a topology optimization procedure that can maximize the bending capability and thus increase the allowable payload of soft grippers that consist of multiple pneumatic bending actuators. After an optimum design is obtained, multiple identical actuators are prototyped through a molding process using a silicone rubber material. Both two-fingered and three-fingered soft grippers are developed using the topology-optimized pneumatic bending actuators. Experiments, including a bending angle test, an output force test, and a payload test, are conducted in this study,and the results are compared against the test results of the commercial SRT soft pneumatic actuator. The experimental results show that the bending angle for the developed bending actuator is 111 degrees on average of 10 tests at an input pressure of 50 kPa. The output force is 9.45 N at an input pressure of 80 kPa, while the maximum payloads of the two-fingered and three-fingered grippers are 2.66 kg and 5.12 kg, respectively.

Simulation Data Driven Design Optimization for Reconfigurable Soft Gripper System

In the soft gripper design work, most of the designs such as gripping width and the design of finger actuator are purely based on experience, and repeated trial-and-error. In most scenarios, the designed actuators cannot achieve the best/optimized grasping performance with a specific design type. This optimized design is important especially for the food grasping application, as a minor improvement of the grasping capability will be helpful to increase the grasping success ratio, especially during high-speed pick and place tasks. That motivates us to develop a design optimization framework, focusing on how to achieve an optimized grasping performance with a multi-objective design optimization. In this work, a simulation aided data-driven optimization framework for guiding the design of a reconfigurable soft gripper system is presented. To achieve an effective optimization, a simulation model is developed based on the Simulation Open Framework Architecture (SOFA) platform. This model can predict the bending and grasping behavior under actuation and external loading. This model is then used in a data-driven design optimization framework for optimizing the actuator design. An artificial neural network (ANN) is built based on the simulation results as training data, and used as a surrogate model in a multi-objective optimization framework, to achieve an optimal grasping capability with design constraints. This simulation and optimization capability can significantly reduce the trial-and-error design work, and has a great potential for effectively developing soft robots in industrial applications, such as food manufacturing and health care.

MORI-A: Soft Vacuum-Actuated Module With 3D-Printable Deformation Structure

Many soft robots are made of polymeric materials such as silicone, urethane, and gel. These soft matter-based robots can be designed to have soft functionality by controlling the deformation, elastic modulus, and other properties of the flexible material. However, updating the shape of a soft robot once it is developed is not considered to be highly effective. It has to be redesigned whenever different functions are required. The body of a modular robot is composed of connected voxel units, and the model and behavior of the robot can be altered conveniently by recombining the module groups. This study proposes a reconfigurable and vacuum-actuated soft matter modular block: MORI-A. It can realize different behaviors of uniaxial bending, shear deformation, and non-deformation depending on the 3D-printed structure contained in a unit. In addition, MORI-A can display elastic anisotropy that depends on the density of the 3D structure it contains and the trajectory it adopts during fabrication. This study quantitatively verifies the load capacity and bendability of MORI-A. We then show that the combination of deformable shapes can improve the diversity of soft modular robot designs by simultaneously developing many curved deformations. These designs include characters. soft modular grippers, applications for underwater swimming robots using curvature, and artificial muscles for dolls made of cloth or cotton that are not supposed to move spontaneously.

Tendon-Driven Soft Robotic Gripper for Blackberry Harvesting

Global berry production and consumption have significantly increased in recent years, coinciding with increased consumer awareness of the health-promoting benefits of berries. Of those consumed, fresh-market blackberries are primarily harvested by hand to maintain postharvest quality. However, the forces applied during hand harvesting can result in major losses of marketable berries to red drupelet reversion (RDR). What is more, manual harvesting is a costly endeavor that accounts for up to 50% of the person-hours involved in berry production. Herein, we present a novel, tendon-driven soft robotic gripper with active contact force feedback control, which leverages the passive compliance of the gripper to allow the gentle harvesting of berries. The versatile gripper can generate a desired force as low as 0.5 N with a mean error of 0.046 N. Field test results indicate that the robotic gripper is capable of harvesting berries with 16% RDR while maintaining a harvesting reliability of 95.24% at a harvesting rate of approximately 4.8 seconds per berry.

A Contact-Triggered Adaptive Soft Suction Cup

Suction adhesion is widely used by natural organisms for gripping irregular objects (e.g., rocks), but their artificial counterparts show less adaptation in the same situation. In addition, they can require complex sensing and control systems to function. In this paper, we present a contact-triggered suction cup with the ability to adapt to objects with complex and irregular shapes. The gripper has two states to adhere and release the object and the transformation from release to adhesion is passively triggered by the contact force, making it an autonomous gripper and removing the need for complex driven system. Once the suction cup experiences a contact force above a set threshold, it will automatically capture the contacting object. Only the resetting transformation from adhesion to release is actuated by a vacuum pump. The maximal suction force up to 15.1 N is generated on the non-flat surface with the suction cup diameter of 30 mm. The performance of this gripper is demonstrated on a 7 DoF robot arm which successfully picked up a variety of irregular objects. We believe that this contact-triggered gripper provides a new solution for low cost, energy-effective and adaptive soft gripping.