Soft Robotic Gripper Research Articles

Hybrid Elastic Organic Crystals that Respond to Aerial Humidity.

Reshaping of elongated organic crystals that can be used as semiconductors, waveguides or soft robotic grippers by application of force or light is now a commonplace, however mechanical response of organic crystals to changes in humidity has not been accomplished yet. Here, we report a universal approach to instigating a humidity response into elastically bendable organic crystals that elicits controllable deformation with linear response to aerial humidity while retaining their physical integrity entirely intact. Hygroresponsive bilayer elements are designed by mechanically coupling a humidity-responsive polymer with elastic molecular crystals that have been mechanically reinforced by a polymer coating. As an illustration of the application of these cladded crystalline actuators, they are tested as active optical transducers of visible light where the position of light output can be precisely controlled by variations in aerial humidity. Within a broader context, the approach described here provides access to a vast range of mechanically robust, lightweight hybrid hygroresponsive crystalline materials.

Nondestructive Dimension Sorting by Soft Robotic Grippers Integrated with Triboelectric Sensor.

In smart logistics, traditional manual sorting and sorting systems based on rigid manipulators limit the warehousing development and damage the goods. Here, a nondestructive sorting method based on bionic soft fingers is proposed. This method is implemented by the soft robotic gripper (SRG) for grasping of the breakable objects, the triboelectric sensor (TES) for size sorting of the objects, and the signal processing module. In the fabrication of SRG, the silicon rubber is prepared by controlling the material synthesis process, and its Young's modulus is 600.91 kPa, which is comparable to the Young's modulus of skin tissue. Also, the maximum input pressure of SRG is 71.4 kPa. The TES has a linear relationship between pulse number and sliding displacement, and its resolution is 3 mm. It induces pulse signal sequences to quantify the SRG bending state and thus realize the size sorting of objects. Additionally, a nondestructive sorting system based on TES and SRG has been developed for fruit sorting (e.g., apples, oranges), enabling nondestructive grasping and accurate sorting. Its sorting range is 70-120 mm, and the sorting accuracy rate is up to 95%. This work also provides a way for the application of SRG and triboelectric sensors in the sorting field.

The design and development of a soft robotic gripper

Soft robots are a unique class of robots, made entirely of soft materials (elastomeric polymers), inspired by animals that do not have hard internal skeletons. Soft robotic structures permits continuous and responsive localized deformation. These properties of soft robots make them suit-able for gripper arms that can be used to handle fragile and delicate objects. In this work, Pnuematic Networks (Pneu-net) are designed in the structure, which is made up of a series of channels and chambers inside an elastomer. These channels inflate when pressurized, creating motion. The material of choice was selected to be LSR220 Series silicone rubber due to its elastic properties and ease of manufacturing. The Computer Aided Design (CAD) model of the actuator is initially developed and then a mold is prepared accordingly for it and we use Rapid Prototyping (RPT) to make the mold. The liquid silicone is then mixed with catalyst and poured in the mold and a plain sheet with cloth embedded in between is prepared for the strain layer. These two layers are then stuck using silicone and when air pressure is supplied, the mismatch strain in layers leads to the bending action of the actuator. Improvements from the traditional silicon-based actuators are tear resistance, uniform pressure distribution, faster and easier manufacturing.

Stiffness-tunable and shape-locking soft actuators based on 3D-printed hybrid multi-materials

Soft actuators have been receiving tremendous attention as a result of their excellent adaptability to the environment. However, due to their inherently low stiffness, soft actuators are difficult to adapt to high-load tasks. Despite previous efforts in developing stiffness-tunable actuators by utilizing variable stiffness materials, they still suffer from limitations, including relatively low load and locking capacity to grasp weights and difficulties regarding their fabrication with complex structures. This work reports a novel stiffness-tunable and shape-locking soft (Tri-S) actuator using hybrid multi-material 3D printing. The Tri-S actuator consists of polylactic acid, thermoplastic polyurethane and a flexible carbon fiber heating wire. Its stiffness can be effectively tuned by Joule heating. A soft robotic gripper equipped with three Tri-S actuators demonstrates their stiffness-tunable and shape-locking capability by grasping and holding objects of various shapes and weights. The gripper can grasp weights up to 2.2 kg with an external driving force by tuning the stiffness and hold weights up to 310 g depending on its own shape locking without an external driving power source.

A Pneumatic Novel Combined Soft Robotic Gripper with High Load Capacity and Large Grasping Range

Pneumatic soft grippers have been widely studied. However, the structures and material properties of existing pneumatic soft grippers limit their load capacity and manipulation range. In this article, inspired by sea lampreys, we present a pneumatic novel combined soft gripper to achieve a high load capacity and a large grasping range. This soft gripper consists of a cylindrical soft actuator and a detachable sucker. Three internal air chambers of the cylindrical soft actuator are inflated, which enables them to hold objects. Under vacuum pressure, the cylindrical soft actuator and the detachable sucker can both adsorb objects. A finite element model was constructed to simulate three inflation chambers for predicting the grasping range of the cylindrical soft actuator. The validity of the finite element model was established by an experiment. The mechanism of holding force and adsorption force were analyzed. Several groups of experiments were conducted to determine adsorption range, holding force, and adsorption force. In addition, practical applications further indicated that the novel combined soft gripper has a high load capacity (10.85 kg) at a low pressure (16 kPa) and a large grasping range (minimum diameter of the object: d = 6 mm), being able to lift a variety of objects with different weights, material properties, and shapes.

Solvent-responsive strong hydrogel with programmable deformation and reversible shape memory for load-carrying soft robot

The development of shape deformation hydrogels has aroused interests of their immense applications in diverse fields such as actuators, soft robotics, and artificial muscles. However, the existing deformable hydrogels can hardly meet the requirements of facile preparation, excellent mechanical properties and reversible shape memory, which greatly limits their further applications. In this work, a new type of fully physically cross-linked deformable hydrogel with mechanically strong, tough, stretchable, and solvent-responsive property is fabricated via free radical polymerization at room temperature, followed by immersed in a Fe3+ aqueous solution. The strong physical interactions of polyacrylic acid (PAA)-Fe3+ metal complexation and hydrogen bond endowed this hydrogel with high tensile strength (~5.14 MPa), high stretchability (~1000%), high toughness (~20.36 MJ/m3) and excellent flexibility (~0.53 MPa). In addition, programmable shape deformation hydrogel is achieved by selective coating of Fe3+ on surface, the hydrogel strips can be deformed into arbitrary shapes such as the letter “o”, “d”, “s”, and “w”. More impressively, reversible shape recovery of hydrogel has been achieved via two methods: the elimination of coated Fe3+ with the reaction of NaOH and the dehydration of the glycerin. Taking advantage of this property, we simulate the closure and opening of hydrogel flower by soaking it into water and NaOH/glycerin alternately. Moreover, the soft robotic gripper has been fabricated based on the mechanically strong and solvent-triggered hydrogel, capable of grabbing about 1.56 times its own weight, which indicating the potential application as load-carrying soft robots.

A Sea-Anemone-Inspired, Multifunctional, Bistable Gripper.

The growing need for soft robots with secure, adaptive, and autonomous functioning in unforeseen environments favors designs with multiple functionalities. This has driven soft robotic grippers to be explored to integrate perceptual capability for augmented multifunctionality. In nature, sea anemones can detect and catch preys of various shapes and sizes effectively with extremely simple bodies because of the efficient coupling of sensing and actuation capability. Inspired by their body structures, we present a bistable gripper with multifunctionality that includes sensing (proprioceptive and exteroceptive) and multimodal gripping (grasping and pinching). The gripper exploits an array of tapered pins on the external surface of a dome membrane for gripping and a set of cylindrical markers on the internal surface of the membrane for optical sensing. The membrane is bistable and can settle in either of two equilibrium states "natural" and "retracted." Gripping functionality is achieved by the centripetal enveloping movement of the pins, along with the passive snap-through process of the membrane. By analyzing the distribution of markers within the view of an embedded camera, sophisticated sensing functionality can be achieved. We first characterized each function separately and then implemented an object handling system, combining the sensing and gripping functionality, to demonstrate the potential for more advanced robotic applications. This work delivers a compact universal gripper design with an efficient and elegant integration of multifunctionality.

Design of a Soft Gripper Using Genetic Algorithms

In this paper, we present an artificial intelligence-assisted design of a soft robotic gripper. First, we formulate the design of the soft gripper as an optimization problem. Then, we design and configure a genetic algorithm (GA) method to solve the problem under design constraints. Lastly, we implement the whole system in co-simulation between the GA and a computer-aided design software that evaluates the candidate solutions using finite element analysis. A network-attached storage server connecting multiple nodes runs the GA method in parallel, to accelerate the process. After experimentation, we present simulation results to validate our approach.

Modeling of Soft Robotic Grippers Integrated With Fluidic Prestressed Composite Actuators

Abstract Soft robotic grippers can gently grasp and maneuver objects. However, they are difficult to model and control due to their highly deformable fingers and complex integration with robotic systems. This paper investigates the design requirements as well as the grasping capabilities and performance of a soft gripper system based on fluidic prestressed composite (FPC) fingers. An analytical model is constructed as follows: each finger is modeled using the chained composite model (CCM); strain energy and work done by pressure and loads are computed using polynomials with unknown coefficients; net energy is minimized using the Rayleigh–Ritz method to calculate the deflected equilibrium shapes of the finger as a function of pressure and loads; and coordinate transformation and gripper geometries are combined to analyze the grasping performance. The effects of prestrain, integration angle, and finger overlap on the grasping performance are examined through a parametric study. We also analyze gripping performance for cuboidal and spherical objects and show how the grasping force can be controlled by varying fluidic pressure. The quasi-static responses of fabricated actuators are measured under pressures and loads. It is shown that the actuators’ modeled responses agree with the experimental results. This work provides a framework for the theoretical analysis of soft robotic grippers and the methods presented can be extended to model grippers with different types of actuation.

Fabrication of a Soft Robotic Gripper With Integrated Strain Sensing Elements Using Multi-Material Additive Manufacturing.

With the purpose of making soft robotic structures with embedded sensors, additive manufacturing techniques like fused deposition modeling (FDM) are popular. Thermoplastic polyurethane (TPU) filaments, with and without conductive fillers, are now commercially available. However, conventional FDM still has some limitations because of the marginal compatibility with soft materials. Material selection criteria for the available material options for FDM have not been established. In this study, an open-source soft robotic gripper design has been used to evaluate the FDM printing of TPU structures with integrated strain sensing elements in order to provide some guidelines for the material selection when an elastomer and a soft piezoresistive sensor are combined. Such soft grippers, with integrated strain sensing elements, were successfully printed using a multi-material FDM 3D printer. Characterization of the integrated piezoresistive sensor function, using dynamic tensile testing, revealed that the sensors exhibited good linearity up to 30% strain, which was sufficient for the deformation range of the selected gripper structure. Grippers produced using four different TPU materials were used to investigate the effect of the Shore hardness of the TPU on the piezoresistive sensor properties. The results indicated that the in situ printed strain sensing elements on the soft gripper were able to detect the deformation of the structure when the tentacles of the gripper were open or closed. The sensor signal could differentiate between the picking of small or big objects and when an obstacle prevented the tentacles from opening. Interestingly, the sensors embedded in the tentacles exhibited good reproducibility and linearity, and the sensitivity of the sensor response changed with the Shore hardness of the gripper. Correlation between TPU Shore hardness, used for the gripper body and sensitivity of the integrated in situ strain sensing elements, showed that material selection affects the sensor signal significantly.

A Soft Robotic Gripper Based on Bioinspired Fingers.

In the past, partly due to modeling complexities and technical constraints, fingers of soft grippers are rarely driven by high number of actuators, which leads to lack of dexterity. Here we propose a soft robotic gripper with modular anthropomorphic fingers. Each finger is actuated by four linear drivers, capable of performing forward/backward bending, and abduction/adduction motions. The piecewise constant curvature kinematic model reveals the proposed finger has an ellipsoidal shell workspace analogous to that of a human finger. Furthermore, we build a gripper using two of our modular fingers, and test dexterity and strength of the finger. Our results show that by simple control schemes, the proposed gripper can perform precision grasps and three types of in-hand manipulations that would otherwise be impossible without the addition actuation.

Fully-Printable Soft Actuator with Variable Stiffness by Phase Transition and Hydraulic Regulations

Actuators with variable stiffness have vast potential in the field of compliant robotics. Morphological shape changes in the actuators are possible, while they retain their structural strength. They can shift between a rigid load-carrying state and a soft flexible state in a short transition period. This work presents a hydraulically actuated soft actuator fabricated by a fully 3D printing of shape memory polymer (SMP). The actuator shows a stiffness of 519 mN/mm at 20 ∘C and 45 mN/mm at 50 ∘C at the same pressure (0.2 MPa). This actuator demonstrates a high stiffness variation of 474 mN/mm (10 times the baseline stiffness) for a temperature change of 30 ∘C and a large variation (≈1150%) in average stiffness. A combined variation of both temperature (20–50 ∘C) and pressure (0–0.2 MPa) displays a stiffness variation of 501 mN/mm. The pressure variation (0–0.2 MPa) in the actuator also shows a large variation in the output force (1.46 N) at 50 ∘C compared to the output force variation (0.16 N) at 20 ∘C. The pressure variation is further utilized for bending the actuator. Varying the pressure (0–0.2 MPa) at 20 ∘C displayed no bending in the actuator. In contrast, the same variation of pressure at 50 ∘C displayed a bending angle of 80∘. A combined variation of both temperature (20–50 ∘C) and pressure (0–0.2 MPa) shows the ability to bend 80∘. At the same time, an additional weight (300 g) suspended to the actuator could increase its bending capability to 160∘. We demonstrated a soft robotic gripper varying its stiffness to carry various objects.

A Soft Robotic Gripper With an Active Palm and Reconfigurable Fingers for Fully Dexterous In-Hand Manipulation

This study is focused on developing a new dexterous soft robotic gripper with three fingers and an active palm capable of performing in-hand manipulation purposes. This innovative design meets all the dexterous manipulation requirements without any increase in mechanical complexity. In each finger, the bending position can be modified and controlled by moving a stiff rod inserted inside the center hole of the finger. In this way, the effective length of the manipulation can be changed. As a result, these reconfigurable fingers provide a more accessible workspace than conventional soft grippers. Besides, a large diversity of the finger's shape configurations results in more dexterity and in-hand manipulation capability. Workspace analysis is accomplished to characterize the advantages of the proposed design. The effectiveness of this soft robotic gripper is validated by different in-hand manipulation experimental tests, including rotation, regrasping, and rolling. The results suggest a promising solution to bridge the design gap between hard and soft robots for dexterous manipulation tasks. The hybrid design carries advantages of these two classes, such as reconfigurability, position, and shape control from hard robots, with large degrees of freedom (DOFs), complex deformations, and lightweight from soft robots. Like human manipulation, the palm plays a major role in stable grasping, especially for enhancing the in-hand manipulation capability. Therefore, we also investigate two types of vacuum palms (suction cup and granular particles) to guarantee a wide range of object manipulation tasks that cannot be completely performed by previously suggested soft grippers.

Proprioceptive Soft Pneumatic Gripper for Extreme Environments Using Hybrid Optical Fibers

Soft pneumatic robotic grippers can be used to conduct a wide range of tasks in extreme environments as they are generally free of conductive or magnetic components. But the sensorization of these grippers can potentially make them unsuitable for such environments and lower their performance through the introduction of electronic components or conductive materials into their structure. This work introduces the design of a sensorized soft pneumatic gripper using hybrid optical fibers making use of rigid and hard segments to measure the bending deformation and the contact force at specific segments of the finger. Using rigid optical fibers, which has low optical loss, for optical signal transmission allows to place all electronic components outside and away from the gripper ensuring the structure of the gripper and its nearby components are non-conductive and non-magnetic. The utilization of rigid reinforcements on the soft pneumatic actuator also helps maintain the performance of the actuator close to existing non-sensorized soft pneumatic actuators. This sensorized actuator is then used in a proprioceptive soft robotic gripper capable of controlling its grasping force.

Probabilistic Modeling and Bayesian Filtering for Improved State Estimation for Soft Robots

State estimation is one of the key requirements in robot control, which has been achieved by kinematic and dynamic models combined with motion sensors in traditional robotics. However, it is challenging to acquire accurate proprioceptive information in soft robots due to relatively high noise levels and hysteretic responses of soft actuators and sensors. In this article, we propose a method of estimating real-time states of soft robots by filtering noisy output signals and including hysteresis in the models using a Bayesian network. This approach is useful in constructing a state observer for soft robot control when both the kinematic model of the actuator and the model of the sensor are used. In our method, we regard a hysteresis function as a conditional random process model. We then introduce a dynamic Bayesian network composed of the actuator and the sensor models of the target system using distribution hysteresis mapping. Finally, we show that solving a Bayesian filtering problem is equivalent to suboptimal state estimation of the soft system. This article describes two ways for defining modeling and filtering; one is by Gaussian process regression combined with an extended Kalman filter, and the other is based on variational inference with a particle filter. While the first approach relaxes the uncertainty level in modeling to Gaussian, the second approach illustrates a general probability distribution. We experimentally validate the proposed methods through real-time state estimation of a sensor-integrated soft robotic gripper. The result shows significant improvement in state estimation compared to conventional estimation methods.

EPM–MRE: Electropermanent Magnet–Magnetorheological Elastomer for Soft Actuation System and Its Application to Robotic Grasping

Conventional soft robotic grippers have been developed based on soft pneumatic actuators or using smart soft materials, but they need external pressure sources, are easily deteriorated or used in millimetric-scale, which leads to increase of the independency, instability, and vulnerability. In this study, we propose an EPM-MRE (Electropermanent Magnet-Magnetorheological elastomer) actuation system, which strengthens the independency and stability of soft actuation by non-contact magnetic force. We established its fundamental principle and investigated parameter design through developing a suction cup as a robotic gripper. We prototyped an EPM-MRE actuated suction cup based on magnetic-charge and tensile modeling as well as optimized the structure of EPM by introducing axisymmetric EPM with frustum pole and suction cup by introducing bi-silicone structure to uniformly activate MRE membrane. The activation of EPM by different current pulses and suction force affected by contact shapes and air gaps were tested. Evaluations showed that the suction cup could be activated with 10 ms and generate a maximum suction force of 9.2 N at a steady state with 0 J energy consumption. In conclusion, the EPM-MRE soft actuation system can be used as a robotic gripper.

A 3D-Printed Fin Ray Effect Inspired Soft Robotic Gripper with Force Feedback.

Soft robotic grippers are able to carry out many tasks that traditional rigid-bodied grippers cannot perform but often have many limitations in terms of control and feedback. In this study, a Fin Ray effect inspired soft robotic gripper is proposed with its whole body directly 3D printed using soft material without the need of assembly. As a result, the soft gripper has a light weight, simple structure, is enabled with high compliance and conformability, and is able to grasp objects with arbitrary geometry. A force sensor is embedded in the inner side of the gripper, which allows the contact force required to grip the object to be measured in order to guarantee successful grasping and to provide the most suitable gripping force. In addition, it enables control and data monitoring of the gripper’s operating state at all times. Characterization and grasping demonstration of the gripper are given in the Experiment section. Results show that the gripper can be used in a wide range of scenarios and applications, such as the service robot and food industry.

A Pneumatically Driven, Disposable, Soft Robotic Gripper Equipped With Multi-Stage, Retractable, Telescopic Fingers

Robots use their end-effectors to grasp and manipulate objects in unstructured and dynamic environments. Robot hands and grippers can vary from rigid and complex designs to soft, inflatable, and lightweight structures. In this paper, we focus on the modeling and development of a pneumatically driven soft robotic gripper with retractable telescopic fingers and finger bases with abduction / adduction capabilities. Both the main fingers and the base actuators use a pre-folded, telescopic structure facilitating passive retraction. The efficiency of the proposed device is experimentally validated through different types of experiments: i) grasping experiments that involve different everyday objects ranging from household objects and fragile items to medical waste and consumables, ii) force exertion experiments that capture the maximum forces that can be exerted by the proposed device when utilizing the different actuators of the gripper, and iii) grasp resistance experiments that focus on the effect of the inflatable structure on resisting environmental uncertainties and disturbances. The proposed gripper is able to grasp a plethora of objects, and can exert more than 14 N of grasping force. The design is so low-cost and modular that the soft fingers and palm pad of the gripper can be used in a disposable manner, facilitating the execution of specialized tasks (e.g., grasping in contaminated environments, handling of medical waste, etc). When it is not inflated, the gripper profile is thin and compact to facilitate storage.

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

While suction cups prevail as common gripping tools for a wide range of real‐world parts and surfaces, they often fail to seal the contact interface when engaging with irregular shapes and textured surfaces. In this work, the authors propose a suction‐based soft robotic gripper where suction is created inside a self‐sealing, highly conformable and thin flat elastic membrane contacting a given part surface. Such soft gripper can self‐adapt the size of its effective suction area with respect to the applied load. The elastomeric membrane covering edge of the soft gripper can develop an air‐tight self‐sealing with parts even smaller than the gripper diameter. Such gripper shows 4 times higher adhesion than the one without the membrane on various textured surfaces. The two major advantages, underactuated self‐adaptability and enhanced suction performance, allow the membrane‐based suction mechanism to grip various three‐dimensional (3D) geometries and delicate parts, such as egg, lime, apple, and even hydrogels without noticeable damage, which can have not been gripped with the previous adhesive microstructures‐based and active suction‐based soft grippers. The structural and material simplicity of the proposed soft gripper design can have a broad use in diverse fields, such as digital manufacturing, robotic manipulation, transfer printing, and medical gripping.

Internally-Balanced Displacement-Force Converter for Stepless Control of Spring Deformation Compensated by Cam With Variable Pressure Angle

The force required to drive a mechanism can be compensated by adding an equivalent load in the opposite direction. By reversing the input and output of the load compensation, we proposed the concept of a displacement-force converter that enables the deformation of the elastic element to be controlled steplessly by a minimal external force. Its principle was proved in our previous study, but challenges arose owing to the use of a wire and pulley. Here, we introduce a new compensation method using a noncircular cam that generates a compensation torque due to the contact force from the follower, which is split in the tangential direction of the cam by the pressure angle varying at rotation. Using a prototype for proof of concept, the maximum control force required for the extension of the spring was successfully reduced by 23.2%. Furthermore, uniform forces were obtained between extension and compression so that the difference between them decreased from 543% to 49% relative to compression. Thus, actuators and current supplies requiring less power could be selected. Moreover, the prototype model was incorporated into a variable stiffness mechanism of a soft robotic gripper as a wire tensioner to show the expandability of the displacement-force converter.