Soft Pneumatic Bending Actuator Research Articles

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.

Continuous deformation analysis and contact force estimation for pneumatic bending actuators interacting with environment

Soft bending actuators show high adaptability for applications such as rehabilitation or grasping. Although constant curvature assumption has been extensively used for free motion modeling, these actuators do not bend circularly when interacting with the environment. In such situation, conventional bending sensors cannot provide useful information on their shape. In this paper, the Finite Rigid Elements approach is utilized to model the behavior of a soft pneumatic bending actuator in free motion and contact. With this method, the variable curvature configuration under different external loads can be modeled. Then, the contact force between the actuator and an object located in a specific position is estimated utilizing the Gradient Descent optimization method. Experimental results verified the combinatorial proposed approach for both force estimation and structure deformation.

Optimizing Out-of-Plane Stiffness for Soft Grippers

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

Segmented Soft Pneumatic Bending Actuator with Artificial Neural Network for Parameter Prediction

Segmented Soft Pneumatic Bending Actuator with Artificial Neural Network for Parameter Prediction

Eccentric High-Force Soft Pneumatic Bending Actuator for Finger-Type Soft Grippers

Abstract Soft pneumatic actuators (SPAs) play an important role in leading the development of soft robotics. However, due to the inherent characteristics of soft materials, the low driving force limits the application of SPAs. This study presents a high-force soft pneumatic bending actuator (SPBA) that consists of a spring, an eccentric silicone cylinder, and a limiting fiber. Based on the Neo-Hookean model, a theoretical model is established to predict the relationship between the bending angle and the pressure of SPBA. Furthermore, we characterize the performance of SPBA in terms of the bending capability, tip force, as well as response time. The results demonstrate the effectiveness of the theoretical model, as well as the high tip force (10.2 N) and fast response capability of SPBA. Finally, SPBAs are used to construct a three-finger soft gripper. The load capacity of the gripper is proofed, which indicates that the gripping force of the gripper increases with the pressure of the fingers and the diameter of the object. The gripping test of the gripper is performed. The result shows that the gripper with the pinching mode can grip objects of various sizes and shapes in the air and underwater, and the gripper with enveloping mode can grip objects with weight up to 1.25 kg.

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.

Optimal Design of Soft Pneumatic Bending Actuators Subjected to Design-Dependent Pressure Loads

Soft actuators, mainly composed of soft materials, have made a great impact on applications in unstructured or unknown environments due to their high flexibility and customizability. The design methods of soft actuators can be divided into two groups: the bionic design method and the topology optimization method. Compared to the bionic design method that requires numerous experiments, the topology optimization method can generate innovative structures according to the design requirements. However, the existing topology optimization method cannot be applied to soft pneumatic bending actuator (SPBA) designs because SPBAs are usually subjected to design-dependent pressure loads of which the position depends on the structure. In this paper, we propose an optimal design framework of SPBAs to resolve the design-dependent load problem using an adaptive bi-directional evolutionary structural optimization method. Herein, SPBAs are considered as compliant mechanisms and our goal is to achieve maximum bending deformation as well as structural stiffness. In finite element analysis, each element in the design domain is set to solid or void according to sensitivity number, which is approximated by the objective function derivative with respect to the design variables. During the iterative optimization procedure, we explicitly define the movable solid-void boundary surfaces on which the pressure will act. A precision prototype actuator is fabricated, and its performance is evaluated in terms of free travel experiment. Some extensions are supplied to validate the optimality and reliability of the proposed method. This framework paves a way for the diversity of soft actuators.

Posture measurement of soft pneumatic bending actuator using optical fibre-based sensing membrane

PurposeSoft robotics is a burgeoning field owing to its high adaptability and safety in human–machine interaction and unstructured environments. However, the feedback control of soft actuators with flexible sensors is still a challenge.Design/methodology/approachTo address this issue, this study proposes an optical fibre-based sensing membrane for the posture measurement of soft pneumatic bending actuators. The major contribution is the development of a flexible sensing membrane with a high sensitivity and repeatability for the feedback control of soft actuators. The characteristics of sensing membrane were analysed. The relationship between wavelength shift and bending curvature was derived. The curvatures of soft actuator were measured at four bending status, and the postures were reconstructed.FindingsThe results indicate that the measurement error is less than 2.1% of the actual bending curvature. The sensitivity is up to 212.8 pm/m−1, and the signal fluctuation in repeated measurements is negligible. This approach has broad application prospects in soft robotics, because it makes the optical fibre achieve more strength and compatible with soft actuators, thus improving the sensing accuracy, sensitivity and reliability of fibre sensors.Originality/valueDifferent from previous approaches, an optical fibre with FBGs is embedded into a multilayered polyimide film to form a flexible sensing membrane, and the membrane is embedded into a soft pneumatic bending actuator as the smart strain limited layer which is able to measure the posture in real time. This approach makes the optical fibre stronger and compatible with the soft pneumatic bending actuator, and the sensing accuracy, sensitivity and reliability are improved. The proposed sensing configuration is effective for the feedback control of the soft pneumatic bending actuators.

A Novel Fold‐Based Design Approach toward Printable Soft Robotics Using Flexible 3D Printing Materials

AbstractSoft robotic technologies have been known to have various advantages over their rigid counterparts due to their compliant and deformable properties. They can carry out delicate object manipulation and perform complex maneuvers in confined spaces, which traditional robotics has difficulty with. The most widely adopted fabrication method for traditional soft elastomeric fluidic actuators is mold‐casting, which is cumbersome and involves several manual steps. Therefore, a substantial variability in performance and quality of these actuators arises directly from the manufacturing process. This paper presents on a novel fold‐based design of a 3D‐printed soft pneumatic bending actuator. In contrast to other works that rely on high‐end multimaterial 3D printers, a consumer‐grade open source 3D printer to fabricate soft pneumatic actuators in a fast and cheap way using fused deposition modeling technology has been adapted. This allows for consistency in both the quality of the actuators and their mechanical performance. The key findings in (1) a 3D‐printed fold‐based actuator fabrication process, (2) actuator characterization, and (3) a design‐centric approach toward different bending profiles for different applications are presented.

Magnetically Assisted Bilayer Composites for Soft Bending Actuators.

This article presents a soft pneumatic bending actuator using a magnetically assisted bilayer composite composed of silicone polymer and ferromagnetic particles. Bilayer composites were fabricated by mixing ferromagnetic particles to a prepolymer state of silicone in a mold and asymmetrically distributed them by applying a strong non-uniform magnetic field to one side of the mold during the curing process. The biased magnetic field induces sedimentation of the ferromagnetic particles toward one side of the structure. The nonhomogeneous distribution of the particles induces bending of the structure when inflated, as a result of asymmetric stiffness of the composite. The bilayer composites were then characterized with a scanning electron microscopy and thermogravimetric analysis. The bending performance and the axial expansion of the actuator were discussed for manipulation applications in soft robotics and bioengineering. The magnetically assisted manufacturing process for the soft bending actuator is a promising technique for various applications in soft robotics.

Soft Pneumatic Bending Actuator with Integrated Carbon Nanotube Displacement Sensor

The excellent compliance and large range of motion of soft actuators controlled by fluid pressure has lead to strong interest in applying devices of this type for biomimetic and human-robot interaction applications. However, in contrast to soft actuators fabricated from stretchable silicone materials, conventional technologies for position sensing are typically rigid or bulky and are not ideal for integration into soft robotic devices. Therefore, in order to facilitate the use of soft pneumatic actuators in applications where position sensing or closed loop control is required, a soft pneumatic bending actuator with an integrated carbon nanotube position sensor has been developed. The integrated carbon nanotube position sensor presented in this work is flexible and well suited to measuring the large displacements frequently encountered in soft robotics. The sensor is produced by a simple soft lithography process during the fabrication of the soft pneumatic actuator, with a greater than 30% resistance change between the relaxed state and the maximum displacement position. It is anticipated that integrated resistive position sensors using a similar design will be useful in a wide range of soft robotic systems.