Soft Bending Actuator Research Articles

Static Model of the Underwater Soft Bending Actuator Based on the Elliptic Integral Function

Underwater soft manipulators are increasingly used for grasping underwater organisms and cultural relics due to their compliance and ability to protect delicate objects. Unlike rigid manipulators, these soft manipulators feature underwater soft bending actuators that deform under external forces, making their shape and output force challenging to predict. Consequently, classical beam theory is no longer applicable. To address these issues, this article models the underwater soft bending actuator as a cantilever beam and establishes its shape and output force using elliptic integral functions. Additionally, this article proposes a method for determining the unknown parameters of the driver shape and output force model using optimization techniques and introduces a solution process based on the particle swarm optimization framework. Given the role of tensile and bending stiffness in the actuator’s performance, this paper employs a parameter identification method based on length and bending angle information. Tests demonstrate that the proposed method effectively estimates the deformation and output force of the underwater soft bending actuators, confirming its accuracy.

Sulphonated-graphene oxide nanocomposite membranes with PVA-ZnO nanostructures and mechanized agitation-enhanced pt coating for soft robotics bending actuator

Ionic Polymer-Metal Composite (IPMC) actuators have garnered significant scientific attention in robotics and artificial muscles for their ability to operate at low voltage, high strain capacity, and lightweight construction. The lack of uniform bending in IPMC actuators undermines their control precision and restricts their range of potential applications. This study utilized the unique properties of nanoscale materials and Polyvinyl alcohol (PVA) to develop a membrane for soft robotic bending actuation. Subsequently, a platinum coating was applied to the membrane to mitigate the limitations of IPMCs in soft robotics applications. Herein, mechanized agitation was employed during the solution-casting process to enhance platinum metal (Pt-metal) coating on zinc oxide (ZnO) nanostructures within a PVA- sulphonated graphene oxide nanocomposite, achieving enhanced soft robotics bending actuation capabilities. The resultant membrane composed of sulphonated-graphene oxide and polyvinyl-zinc oxide coated with pt (PsGZ-Pt) was examined by exploring advanced analytical techniques such as Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction spectroscopy (XRD). Furthermore, the ionic exchange capacity (IEC), proton conductivity (PC), water uptake and water loss characteristics were evaluated to be 2.1 meq. g−1, 1.95 × 10−3 Scm−1, 59.62% at 45 °C and water loss at 9 min immersion found 38%, respectively. Electromechanical studies of the PsGZ-Pt membrane (size 30 mm length, 10 mm width, 0.07 mm thickness) showed an actuation force of 0.3253 mN and a displacement of roughly 22.8 mm at ± 3 VDC. These findings highlighted the PsGZ-Pt membrane’s potential as a low-cost alternative to expensive commercial IPMC actuators based on polymers. These results presented a straightforward, low-cost approach for synthesizing PsGZ-Pt utilizing conventional technologies. The PsGZ-Pt membrane shows promise for generating low-cost, high-performance actuation materials with a wide range of industrial applications.

Development of a novel variable-curvature soft gripper used for orientating broccoli in the trimming line

Orientating the broccoli plays an important part in the trimming line, which helps reduce the redundant stalk length and provides accurate throughput data for sale. However, this work is still manual with high labor intensity and low work efficiency, and current grippers show limitations in replacing manual operations, which need the ability to self-adaptively grasp broccoli without damage and guide them upright. This study presented a novel pneumatic variable-curvature soft gripper (VCSG) for orientating broccoli, which mainly comprised three soft variable-curvature fiber-reinforced bending actuators (VCFRBAs). The VCFRBAs can generate additional lifting forces to help guide the broccoli upright, thus orientating the broccoli. A design concept was built for the VCFRBA, and an analytical model and finite element method (FEM) were proposed to evaluate the bending deformation of VCFRBA, achieving a good match with a root mean squared error of below 5.8°. Step response tests of VCFRBA showed a response time of 0.35 s, hysteresis tests demonstrated a hysteresis error of less than 10 %, and durability tests in 5,000 cycles showed two error bands of both less than 5 %, indicating a fast response, good repeatability, and good durability, respectively. Single actuator force experiments demonstrated the VCFRBA can generate a clamping force of 1.13 N with an additional lifting force of 1.38 N when grasping under the pressure of 0.2 MPa. Furthermore, a maximum pull-off force of 35.06 N was measured for the VCSG at this pressure. Results of grasping experiments showed a 100 % success rate without damage when the VCSG grasped broccoli positioned upright, and broccoli can still be securely and self-adaptively grasped and guided upright when grasping them inclinedly. Further orientating tests suggested that the VCSG had a good performance with an 85 % success rate. These results demonstrate that the proposed VCSG has a good ability to orientate the broccoli self-adaptively without complex operations. This study showcases a novel VCSG, providing a unique solution to orientating broccoli in the trimming line.

Piezoresistive properties for soft structures using hybrid CCB/CNT-based natural rubber latex composites

This study explores the development of flexible sensors for soft structures. Conductive carbon black (CCB) and carbon nanotubes (CNT) were incorporated into a natural rubber (NR) matrix using glutaraldehyde (GA) as a curing system. The sensor properties of latex-NR composites with 20 phr of CCB, including variations of CNT content (0.5 to 3 phr), were examined. Increasing CNT content beyond 0.5 phr decreased tensile strength and elongation at break, but improved sensitivity and gauge factor (GF). Additionally, applying a voltage over 5 V caused a joule heating of the latex-NR composite strip elements. When integrated onto a soft tendon-based TPU bending actuator, higher CNT content reduced electrical signal drift during cyclic bending, enhancing long-term monitoring. This research highlights the potential of CCB/CNT-based latex-NR composites for soft structure applications, including soft robotics and health monitoring.

Soft Electrohydraulic Bending Actuators for Untethered Underwater Robots

Traditional underwater rigid robots have some shortcomings that limit their applications in the ocean. In contrast, because of their inherent flexibility, soft robots, which have gained popularity recently, offer greater adaptability, efficiency, and safety than rigid robots. Among them, the soft actuator is the core component to power the soft robot. Here, we propose a class of soft electrohydraulic bending actuators suitable for underwater robots, which realize the bending motion of the actuator by squeezing the working liquid with an electric field. The actuator consists of a silicone rubber film, polydimethylsiloxane (PDMS) films, soft electrodes, silicone oils, an acrylic frame, and a soft flipper. When a square wave voltage is applied, the actuator can generate continuous flapping motions. By mimicking Haliclystus auricula, we designed an underwater robot based on six soft electrohydraulic bending actuators and constructed a mechanical model of the robot. Additionally, a high-voltage square wave circuit board was created to achieve the robot’s untethered motions and remote control using a smart phone via WiFi. The test results show that 1 Hz was the robot’s ideal driving frequency, and the maximum horizontal swimming speed of the robot was 7.3 mm/s.

Model-based linear control of nonlinear pneumatic soft bending actuators

Advanced model-based control techniques hold great promise for the precise control of pneumatic soft bending actuators (PSBAs) with strong nonlinearities. However, most previous controllers were designed in a cumbersome nonlinear form. Considering the simplicity of linear system theory, this paper presents a novel perspective on using model-based linear control to handle nonlinear PSBAs, and for the first time, summarizes two methodologies, global linearization and pseudo-linear construction. Derived from them, Koopman-based and hysteresis-based linear control approaches are proposed, respectively. For the former, a novel fusion prediction equation is developed to build a high-fidelity Koopman model, realizing global linearization, and then the linear model predictive control (MPC) is deployed. For the latter, the inverse of the generalized Prandtl–Ishlinskii (GPI) model cascades with the PSBA to construct a pseudo-linear system, eliminating the asymmetric hysteresis, which activates the linear proportional-integral-derivative (PID) control. It is worth noting that the above two are based on data-driven models adapted to various PSBAs with material and structural customization. Finally, the two model-based linear control approaches are verified and compared through a series of experiments. The results show that the proposed linear controls, with more concise designs, achieve comparable or even superior performance than nonlinear controls.

Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

A soft fiber-reinforced bending actuator (SFRBA) is a multi-material system that plays a crucial role in robotics applications due to its high output force and robust bending motion. However, the multi-material composition of SFRBAs causes significant structural nonlinearity. This nonlinear behavior is difficult to capture using traditional analytical models. This study presents a method for modeling the SFRBA using finite element method (FEM) and nonlinear machine learning algorithms (MLAs). First, the key structural parameters of the SFRBA are defined and selected as input variables for the method. An accurate FEM, considering varying actuation pressure, is then employed to generate a simulation training dataset. Subsequently, three nonlinear MLAs, including polynomial regression (PLR), extreme gradient boosting regression (XGBoostR), and normalized multilayer perceptron regression (NMLPR), are developed to model the bending angle of the SFRBA. Moreover, transfer learning is deployed to improve the accuracy and convergence speed of the optimal NMLPR. Experimental measurements are conducted to validate the established MLAs, and the results demonstrate that the refined NMLPR outperforms the other models, yielding an average Root Mean Square Error (RMSE) of 7.935° and Mean Absolute Percentage Error (MAPE) of 6.45%. Furthermore, the refined NMLPR is implemented in a feedback control loop to showcase its real-time ability to convert actuation pressure information into bending angles. The results exhibit excellent control performance, with an average MAPE of less than 6% and a low time delay of 0.0875 s. This work exemplifies a methodology that combines FEM and MLAs for modeling SFRBAs, paving the way for their further development and practical application.

High-temperature electromechanical actuation of relaxor ferroelectric polymers blended with normal ferroelectric polymer

Soft actuators that can operate at high temperatures are of great interest in emerging research fields such as microfluidics, soft robotics, automotive, aircraft, and bioelectronics. However, most polymer-based flexible actuators suffer from performance degradation at elevated temperatures above 60 °C. In this paper, we present the high-temperature electromechanical actuation of relaxor ferroelectric polymers solution-blended with normal ferroelectric polymers. We conduct a systematic analysis of the electromechanical properties of three unimorph actuators with relaxor ferroelectric poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene)s [P(VDF-TrFE-CFE)s] containing different amounts of chlorofluoroethylene (CFE) moieties (approximately 1, 3.5, and 9 wt%). In this study, we propose the film stress, given as Young's modulus times strain, as the measure of the electromechanical performance of soft bending actuators under loading, rather than strain or strain energy density. We demonstrate that a relaxor ferroelectric actuator with 1-wt% CFE, which mixes high-modulus ferroelectric crystal domains with an optimized electrostrictive relaxor phase, develops a high film stress of ∼3.5 MPa. When blended with the normal ferroelectric P(VDF-TrFE), the actuator exhibits excellent film stress of approximately 3.1 MPa at an elevated temperature of 60 °C comparable with that at 25 °C. The high-modulus ferroelectric crystals in P(VDF-TrFE) reinforce the mechanical properties of the actuator at elevated temperatures, generating high-temperature electromechanical actuation with a large strain and strain energy density of approximately 1.6% and 23 mJ/cm², respectively. We also demonstrate successful microfluidic pump operation at 60°C with our actuator using a relaxor ferroelectric polymer blended with an intrinsic ferroelectric polymer.

Soft Bending Actuator With Fiber-Jamming Variable Stiffness and Fiber-Optic Proprioception

Soft Bending Actuator With Fiber-Jamming Variable Stiffness and Fiber-Optic Proprioception

Mechanisms boosting material embodied intelligence to realize self-healing soft robots

The recent introduction of self-healing soft materials in robotics is a major step towards sustainable next generation robots. By manufacturing soft robots out of these smart materials, we integrate a self-healing ability and increase the physical intelligence of these systems. However, the embodied intelligence in the material level needs to be augmented by incorporating assistive mechanisms in the system level with minimized control, enabling healing of damage in different sizes and in diverse working conditions. These assistive mechanisms can provide damage detection, damage closure, healing stimuli providing, health monitoring, or a combination of the previous. In this paper, we present two different mechanisms for an autonomous healing of damages; (i) Embedding a healable heater in a self-healing soft actuator to increase the temperature required for an efficient healing, while it allows detecting the damage and monitoring the health of the system. (ii) Incorporating shape memory alloy wires in a self-heling soft bending actuator, with simultaneous sealing through contraction and heating abilities. Apart from assisting in the healing action, both mechanisms play a part in the actuation of the bending robots as strain limiting elements. These assistive mechanisms will overcome the limitation on the material level, leading to robots that can self-heal in applications outside of laboratories and factories.

Bending analysis of a soft pneumatic actuator using analytical and numerical methods

Soft bending actuators have applications in many areas where it is required to have compliant and safer interaction to deal with delicate objects. Soft bending actuators are being used in soft robots and in wearable medical devices for rehabilitation. Soft bending actuators are generally actuated using pneumatic air pressure because it provides cleaner, simple and safer operations while dealing with delicate objects and human. For efficient control of a soft pneumatic actuator (SPA), it is essential to have its mathematical model which directly affects the design criteria. The analytical modeling of such highly flexible and compliant SPA is challenging due to nonlinearity in the geometrical and material properties. This study focuses on the analytical modeling of a SPA for analyzing its bending behavior under application of the input pneumatic pressure. The estimated bending results of the analytical model are compared and verified with the numerical method i.e., finite element analysis (FEA). The bending results obtained from the analytical model showed high error when compared with the FEA results. Therefore, in this work, the analytical model is modified by using a linear correction term in the model. As a result of that, the error between the analytical and the numerical methods is significantly reduced.[copyright information to be updated in production process]

Evolution from Telescoping to Bending: An Origami-Inspired Flexible Bending Actuator

Soft actuators have great potential in human–machine interaction and soft robotics innovation. Origami exhibiting outstanding structural and topological properties can be a paradigm for people to design various soft robots. Inspired by origami, we have previously designed a telescopic actuator with excellent performance, mainly large force output, and two-way working. Although significant advances have been made in soft bending actuators, their further study and applications are limited due to small force output in a monotonous work style. In this paper, we design a series of novel bending actuators that inherit our prior telescopic actuator’s excellent characteristics to diversify soft actuators’ motion forms. Several actuators of different sizes are fabricated using three different materials and evaluated on a designed test platform. The test results show that actuators of different sizes using different materials perform differently. Namely, the maximum tip force produced by an actuator reaches 9.6 N, and the maximum bending angle is achieved by another one up to 138°. Finally, extensive demonstrations and tests include wriggling, gripping, and bidirectional motion in the water. They show our flexible bending actuators’ distinguishing characteristics of large output force and two-way working.

Development of an Active Physical Interface for Physical Human-Robot Interaction: Investigation of Soft Pneumatic Actuator Straps for Automatic Enclosure System

Wearable robots have become increasingly prevalent in various applications, including rehabilitation, power augmentation, and assistance. However, one of the challenges in designing wearable robots is how to attach them to the human body. The attachment method should be secure, reliable, comfortable, effective, and controlled for the user. Moreover, the attachment points should not interfere with the user’s daily activities, and the attachment process should not be time-consuming or complicated. Typical straps nowadays require a time-consuming and cumbersome donning and doffing procedure from therapists for users needing rehabilitation therapy. Therefore, we propose a novel pneumatically actuated soft strap to enclose the limb and automate part of the strapping procedure. This paper proposes a preliminary design utilizing soft bending actuators for attaching physical interfaces to humans, with integrated active elements for facilitating and automating the strapping process. Finite element analysis was conducted to assess pressure requirements, bending curvature, and geometry, with simulation results demonstrating a promising agreement, with a root mean square error (RMSE) of 3.4° in bending angle. In the future, an additional locking mechanism would be required to provide the necessary holding force and fully constrain the limb.

Assisted damage closure and healing in soft robots by shape memory alloy wires

Self-healing soft robots show enormous potential to recover functional performance after healing the damages. However, healing in these systems is limited by the recontact of the fracture surfaces. This paper presents for the first time a shape memory alloy (SMA) wire-reinforced soft bending actuator made out of a castor oil-based self-healing polymer, with the incorporated ability to recover from large incisions via shape memory assisted healing. The integrated SMA wires serve three major purposes; (i) Large incisions are closed by contraction of the current-activated SMA wires that are integrated into the chamber. These pull the fracture surfaces into contact, enabling the healing. (ii) The heat generated during the activation of the SMA wires is synergistically exploited for accelerating the healing. (iii) Lastly, during pneumatic actuation, the wires constrain radial expansion and one-side longitudinal extension of the soft chamber, effectuating the desired actuator bending motion. This novel approach of healing is studied via mechanical and ultrasound tests on the specimen level, as well as via bending characterization of the pneumatic robot in multiple damage healing cycles. This technology allows soft robots to become more independent in terms of their self-healing capabilities from human intervention.

Design of a Bistable Artificial Venus Flytrap Actuated by Low Pressure with Larger Capture Range and Faster Responsiveness.

The rapid closure of the Venus flytrap (Dionaea muscipula) can be completed within 0.1-0.5 s due to the bistability of hyperbolic leaves and the curvature change of midrib. Inspired by its bistable behavior, this paper presents a novel bioinspired pneumatic artificial Venus flytrap (AVFT), which can achieve a larger capture range and faster closure action at low working pressure and low energy consumption. Soft fiber-reinforced bending actuators are inflated to move artificial leaves and artificial midrib fabricated from bistable antisymmetric laminated carbon fiber-reinforced prepreg (CFRP) structures, and then the AVFT is rapidly closed. A two-parameter theoretical model is used to prove the bistability of the selected antisymmetric laminated CFRP structure, and analyze the factors affecting the curvature in the second stable state. Two physical quantities, critical trigger force and tip force, are introduced to associate the artificial leaf/midrib with the soft actuator. A dimension optimization framework for soft actuators is developed to reduce their working pressures. The results show that the closure range of the AVFT is extended to 180°, and the snap time is shortened to 52 ms by introducing the artificial midrib. The potential application of the AVFT for grasping objects is also shown. This research can provide a new paradigm for the study of biomimetic structures.

Tuning Stiffness with Granular Chain Structures for Versatile Soft Robots.

Stiffness variation can greatly enhance soft robots' load capacity and compliance. Jamming methods are widely used where stiffness variation is realized by jamming of particles, layers, or fibers. It is still challenging to make the variable stiffness components lightweight and adaptive. Besides, the existing jamming mechanisms generally encounter deformation-induced softening, restricting their applications in cases where large deformation and high stiffness are both needed. Herein, a multifunctional granular chain assemblage is proposed, where particles are formed into chains with threads. The chain jamming can be classified into two types. Granular chain jamming (GCJ) utilizes typical particles such as spherical particles, which can achieve both high stiffness and great adaptability while keeping jamming components relatively lightweight, while by using cubic particles, a peculiar deformation-induced stiffening mechanism is found, which is termed as stretch-enhanced particle jamming (SPJ). The versatility of GCJ and SPJ mechanisms in soft robots is demonstrated through soft grippers, soft crawlers, or soft bending actuators, where great passive adaptability, high load capacity, joint-like bending, friction enhancement, or postponing buckling can be realized, respectively. This work thus offers a facile and low-cost strategy to fabricate versatile soft robots.

Transforming Soft Robotics: Laminar Jammers Unlocking Adaptive Stiffness Potential in Pneunet Actuators

PneuNet actuators emulate human finger function and have broad application potential in domestic and industrial settings. To unlock their full potential, enhancing their controlled stiffness is crucial. This study presents the innovative design, fabrication, and evaluation of a cost-effective soft hybrid bending actuator by merging a homogeneous laminar structure, composed of 75 GSM printer paper, with a PneuNet actuator produced through soft lithography techniques. This research also characterizes the ensemble based on its tunable stiffness properties and examines the friction tests on jamming layers, highlighting the stabilization of frictional properties over time, which is critical for achieving consistent tunable stiffness. Experiments revealed that the actuator’s resistive force increases due to deformation when subjected to an external load. Furthermore, this linear rise in resistive force can be modulated through the use of an integrated laminar jammer by adjusting the vacuum pressure. Results reveal a negligible stiffness increase beyond −53.33 kPa of vacuum pressure, signifying an ideal vacuum pressure limit for energy conservation during vacuum jamming. A maximum stiffness of 0.116 N was achieved at −80 kPa of vacuum pressure. This study propels the field of soft robotics by offering enhanced tunable stiffness characteristics for diverse applications.

A Hierarchical Design Framework for the Design of Soft Robots

This paper demonstrates the effectiveness of a hierarchical design framework in developing environment-specific behaviour for fluid-actuated soft robots. Our proposed framework employs multi-step optimisation and reduced-order modelling to reduce the computational expense associated with simulating non-linear materials used in the design process. Specifically, our framework requires the designer to make high-level decisions to simplify the optimisations, targeting simple objectives in earlier steps and more complex objectives in later steps. We present a case study, where our proposed framework is compared to a conventional direct design approach for a simple 2D design. A soft pneumatic bending actuator was designed that is able to perform asymmetrical motion when actuated cyclically. Our results show that the hierarchical framework can find almost 2.5 times better solutions in less than 3% of the time when compared to a direct design approach.

A Novel and Practicable Approach for Determining the Beam Parameters of Soft Pneumatic Multi-Chamber Bending Actuators

The design of many pneumatic soft actuators is based on multiple chambers in parallel alignment. The Cosserat beam theory is an established technique for modeling this kind of actuator, where existing approaches mainly differ in the parameters being required for simulation. The modeling approach presented in this study particularly aims at finding the beam parameters necessary for a simulation even with limited experimental methods. Importantly, it provides a straightforward relationship between the bending stiffness, the extensional stiffness and the axial stretch of the actuator. If the actuator to be modeled has an elementary design, axial measurements are sufficient to identify the parameters to perform three-dimensional simulations, which is of interest to adopters with limited testing equipment. The experimentally parameterized model of such an actuator of elementary design shows high accuracy. Both without load and with a weight of 1N applied to the tip, the mean error of the tip position in vertical orientation is less than 3.4% for a constant extensional stiffness and less than 2.7% for a pressure-dependent extensional stiffness. Further reduction of the error could be achieved by more refined identification techniques that decompose the complex interrelationship of pressurization, forces and material stiffness.

Characterization of hyperelastic materials for manufacturing soft bending actuators

Unlike rigid link robots, the geometry and material properties of soft-bending actuators play an important role in preprogramming their bending behavior. The material properties of low-shore hardness silicones can be approximated through mathematical models of hyperelastic materials and can be determined experimentally using uniaxial and planer biaxial testings. This article investigates the bending behavior of soft actuators of similar geometry made of Elastosil M4601 and Smoothsil 950. Yeoh and NeoHookean mathematical models were selected to investigate the designed actuators in Abaqus simulation software. The effect of change in internal pneumatic pressures on the bending angles of actuators is investigated through simulations. Further, the bending behavior has also been investigated to verify the impact of strain-limiting layers. The results indicate that Elastosil M4601 is more sensitive to internal pressure and is suitable for low-pressure applications compared to Smoothsil 950. Comparisons between pneunets with and without strain layers indicate that there is a minimum or no effect of strain layer on the bending performance of the actuator with open wall configuration.