Pneumatic Artificial Muscles Research Articles

Development of an innovative quasi-zero stiffness oscillation model using pneumatic artificial muscle

The paper proposes an innovative nonlinear oscillation model having potential benefits in engineering application such as vibration isolation, vibration absorber and so forth. This model composes four offset slider-crank mechanism and four cam mechanism, whose main feature is to remain the quasi-zero stiffness value within the working region. Furthermore, instead of using conventional elastic elements such as coil spring, rubber air spring, etc. Another potential elastic element which is pneumatic artificial muscle (PAM) will be introduced in this work. Indeed, the PAM can work as a spring for supporting the load simultaneously it may also work as an actuator for creating active force. This means that the proposed model can be changed easily between two working modes such as passive and active one. First of all, the restoring model of a commercial PAM will be analyzed and identified experimentally. Based on these results, an offset slider-crank mechanism is then designed, next designing the cam mechanism will be presented. The constraint of this design is that vertical restoring force of the proposed oscillation model is always constant in working region, attaining the quasi-zero stiffness. The result is to obtain a set of equations describing the profile of the cam. From these equations, a 3D model of the cam mechanism will be built. Finally, a prototype of the proposed model will be fabricated and realized experimentally. The experimental result confirmed the agreement between the measured and simulated data, meaning that the proposed model can offer a constant force-displacement or quasi-zero stiffness curves in working region. This study will offer a useful insight into the dynamic analysis of this oscillation model.

Experimental analysis of biomimetic silencer to reduce exhaust noise in pneumatic devices

Pneumatic devices such as pneumatic artificial muscles (PAMs) generate excessive noise during operation, thus inducing safety hazards and becoming a nuisance to nearby communities. In this study, biomimetic silencers consisting of polyurethane foam and slit structures that mimic shark gill slits to reduce the exhaust noise caused by pneumatic devices were developed and experimentally analyzed. Two separate experimental approaches were employed to evaluate and analyze the performance of the developed biomimetic silencer. During these experiments involving the compressor and PAM exhaust noise measurements, the sound pressure signals, noise, and flow rate were obtained for the cases of with and without silencer. The results demonstrated that the slit structure of the developed silencer decreased the relative velocity with the surrounding air, thus resulting in approximately 6 dB improvement in noise reduction performance of the developed silencer compared with that of a general pneumatic silencer. Although the use of porous materials in the silencer causes an exhaust time delay, the delay is insignificant compared with that of a general pneumatic silencer in terms of the exhaust area. Thus, the developed silencer is an effective solution for reducing the exhaust noise in pneumatic devices, particularly in situations where noise reduction is critical.

Design, Modelling, and Control of Continuum Arms with Pneumatic Artificial Muscles: A Review

In this research paper, we present a comprehensive analysis of the current state of soft robots actuated with pneumatic artificial muscles and emphasise their distinct advantages over rigid robots, including exceptional flexibility, adaptability, and safety. Our study explores the design principles of soft robots, drawing inspiration from biological systems and human hands, and identifies promising avenues for further development. The emergence of hybrid robots is also recognised as a significant advancement, particularly in scenarios requiring high precision. The article explores mathematical models encompassing kinematics, dynamics, and statics, as well as alternative model-free approaches. These theoretical frameworks are instrumental in understanding and manipulating the behaviour of soft robots. However, despite substantial progress, soft robots’ practical application and simulation face limitations, primarily due to the demanding requirements and implementation challenges associated with their deployment. Consequently, this paper highlights the need for continued research and advancements to bridge the gap between the theoretical potential and practical utilisation of soft robots.

Sarcomere‐Inspired Multilayer Artificial Muscle Units for Hyperconfigurable Robotic Applications

Soft pneumatic biomimetic robotic systems excel at the specific application they are designed for, often to interact or navigate unstructured environments safely. However, redeployment to new purposes requires substantial resources, from redesign to revalidation. Despite most pneumatic artificial muscles surpassing the power and contraction performance of natural muscles, natural muscles largely remain unmatched in terms of their versatility and complex performance. This is likely due to artificial muscle's low effective strain and high radial expansion, limiting parallel operating efficiencies. To address these challenges, a class of compact versatile pneumatic actuators, called multilayer artificial muscle (MAM), that are capable of deployment to different applications through configurable modularity, is presented. The MAMs are biomimetically inspired by the sarcomere, the building block for natural muscle architecture. Similarly, MAM can extend and contract as well as be rearranged to mimic muscle‐like actions and functions, such as a caterpillar locomotion robot and an entire robotic arm. The MAMs are fabricated through multilayer, multimaterial, low‐cost additive manufacturing, which offers certain advantages such as higher extension, contraction force, and durability. MAMs have the potential to provide a crucial fundamental building block toward future versatile reconfigurable architecture.

Nonlinear response and fluctuating torque characteristics of the pneumatic muscle actuators at crankshaft application

The present study aims to investigate the availability of pneumatic muscle actuators (PMAs) for producing continuous rotational motion by simulating a crankshaft drive system actuated by artificial muscles. It examines the nonlinear behavior and fluctuating torque characteristic of the PMAs in the crankshaft drive system over the experimentally determined tensile forces. It also looks at the effects of the joint structure, the contraction rate, the timing of the pressurization, the use of a mechanical stopper, and the number of PMAs. It identifies and examines five design versions, including the variations of these parameters. It investigates the range of these parameters for an ideal configuration of the PMA-based crankshaft drive system. The results showed that 44.9 N·m average crankshaft torque fluctuating between 18 and 81.4 N·m is achievable using DMSP-20-300 PMAs at 600 kPa air pressure. Regarding continuous rotational motion, the crankshaft application differs from the PMA-based studies in the literature. The proposed approach fills a gap in the spectrum of activation technologies since it converts linear stroke into continuous and fluctuated rotational output through intermittent oscillating pulling motion generated by a single pneumatic artificial muscle.

X-crossing pneumatic artificial muscles.

Artificial muscles are promising in soft exoskeletons, locomotion robots, and operation machines. However, their performance in contraction ratio, output force, and dynamic response is often imbalanced and limited by materials, structures, or actuation principles. We present lightweight, high-contraction ratio, high-output force, and positive pressure-driven X-crossing pneumatic artificial muscles (X-PAMs). Unlike PAMs, our X-PAMs harness the X-crossing mechanism to directly convert linear motion along the actuator axis, achieving an unprecedented 92.9% contraction ratio and an output force of 207.9 Newtons per kilogram per kilopascal with excellent dynamic properties, such as strain rate (1603.0% per second), specific power (5.7 kilowatts per kilogram), and work density (842.9 kilojoules per meter cubed). These properties can overcome the slow actuation of conventional PAMs, providing robotic elbow, jumping robot, and lightweight gripper with fast, powerful performance. The robust design of X-PAMs withstands extreme environments, including high-temperature, underwater, and long-duration actuation, while being scalable to parallel, asymmetric, and ring-shaped configurations for potential applications.

Funabot-Suit: A bio-inspired and McKibben muscle-actuated suit for natural kinesthetic perception

In recent years, there has been extensive utilization of actuators driven by artificial muscles in wearable devices. However, the muscle distribution configurations of most wearable devices have been specifically designed and are difficult to generalize. Consequently, wearable devices that allow direct installation of actuators onto existing clothing are better suited for a wider range of application scenarios. This letter presents the development and evaluation of Funabot-Suit, a human muscle configuration inspired wearable assist device that employs McKibben artificial muscles to induce natural kinesthetic perception in the wearer’s torso. By integrating thin McKibben muscles into an existing motion capture suit, the Funabot-Suit is capable of generating four fundamental motions: forward and backward bending, and left and right twisting. The suit’s performance was assessed through experiments involving three subjects who wore the suit while standing and seated, with the subjects reporting the direction of their kinesthetic perception. The subjects also rated the perceived ease of kinesthetic perception direction on a five-point scale. Our results demonstrate that the Funabot-Suit successfully induces kinesthetic perceptions for the wearer, with a one hundred percent detection ratio for accurate responses in the command direction across all subjects and positions. We observed variations in the sensitivity of left–right and up-down sensations, which can be attributed to the positioning of artificial muscles and individual differences.

Back-Stretchable McKibben Muscles: Expanding the Range of Antagonistic Muscle Driven Joints

Back-Stretchable McKibben Muscles: Expanding the Range of Antagonistic Muscle Driven Joints

Thermo-Pneumatic Artificial Muscle: Air-Based Thermo-Pneumatic Artificial Muscles for Pumpless Pneumatic Actuation.

To make robots more human-like and safer to use around humans, artificial muscles exhibiting compliance have gained significant attention from researchers. However, despite having excellent performance, pneumatic artificial muscles (PAMs) have failed to gain significant traction in commercial mobile applications due to their requirement to be tethered to a pneumatic source. This study presents a thermo-PAM called Thermo-PAM that relies on heating of a volume of air to produce a deformation. This allows for pneumatic actuation using only an electrical power source and thus enables pumpless pneumatic actuation. The actuator uses a high ratio between the heating volume and the deformable volume to produce a high actuation force throughout its entire motion and can produce either contractile or extension motions. The controllability of the actuator was demonstrated as well as its ability to handle heavy payloads. Moreover, it is possible to rely on either positive or negative pressure actuation modes where the positive pressure actuation mode actuates when heated and the negative pressure actuation mode relaxes when heated. The ability to use Thermo-PAMs for different modes of actuation with different operation methods makes the proposed actuator highly versatile and demonstrates its potential for advanced pumpless robotic applications.

Sliding mode control of antagonistically coupled pneumatic artificial muscles using radial basis neural network function

This study presents a novel approach to enhance the control of Pneumatic Artificial Muscle (PAM) systems by combining Sliding Mode Control (SMC) with the Radial Basis Function Neural Network (RBFNN) algorithm. PAMs, when configured antagonistically, offer several advantages in creating human-like actuators. However, their inherent nonlinearity and uncertainty pose challenges for achieving precise control, especially in rehabilitation applications where control quality is crucial for safety and efficacy. To address these challenges, we propose an RBF-SMC approach that leverages the nonlinear elimination capability of SMC and the adaptive learning ability of RBFNN. The integration of these two techniques aims to develop a robust controller capable of effectively dealing with the inherent disadvantages of PAM systems under various operating conditions. The suggested RBF-SMC approach is theoretically verified using the Lyapunov stability theory, providing a solid foundation for its effectiveness. To validate its performance, extensive multi-scenario experiments were conducted, serving as a significant contribution of this research. The results demonstrate the superior performance of the proposed controller compared to conventional controllers in terms of convergence time, robustness, and stability. This research offers a significant contribution to the field of PAM system control, particularly in the context of rehabilitation. The developed RBF-SMC approach provides an efficient and reliable solution to overcome the challenges posed by PAMs’ nonlinearity and uncertainty, enhancing control quality and ensuring the safety and efficacy of these systems in practical applications.

Soft Pneumatic Muscles: Revolutionizing Human Assistive Devices with Geometric Design and Intelligent Control.

Soft robotics, a recent advancement in robotics systems, distinguishes itself by utilizing soft and flexible materials like silicon rubber, prioritizing safety during human interaction, and excelling in handling complex or delicate objects. Soft pneumatic actuators, a prevalent type of soft robot, are the focus of this paper. A new geometrical parameter for soft artificial pneumatic muscles is introduced, enabling the prediction of actuation behavior using analytical models based on specific design parameters. The study investigated the impact of the chamber pitch parameter and actuation conditions on the deformation direction and internal stress of three tested soft pneumatic muscle (SPM) models. Simulation involved the modeling of hyperelastic materials using finite element analysis. Additionally, an artificial neural network (ANN) was employed to predict pressure values in three chambers at desired Cartesian positions. The trained ANN model demonstrated exceptional performance. It achieved high accuracy with training, validation, and testing residuals of 99.58%, 99.89%, and 99.79%, respectively. During the validation simulations and neural network results, the maximum errors in the x, y, and z coordinates were found to be 9.3%, 7.83%, and 8.8%, respectively. These results highlight the successful performance and efficacy of the trained ANN model in accurately predicting pressure values for the desired positions in the soft pneumatic muscles.

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

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

Development of split-force-controlled body weight support (SF-BWS) robot for gait rehabilitation.

This study introduces a body-weight-support (BWS) robot actuated by two pneumatic artificial muscles (PAMs). Conventional BWS devices typically use springs or a single actuator, whereas our robot has a split force-controlled BWS (SF-BWS), in which two force-controlled actuators independently support the left and right sides of the user's body. To reduce the experience of weight, vertical unweighting support forces are transferred directly to the user's left and right hips through a newly designed harness with an open space around the shoulder and upper chest area to allow freedom of movement. A motion capture evaluation with three healthy participants confirmed that the proposed harness does not impede upper-body motion during laterally identical force-controlled partial BWS walking, which is quantitatively similar to natural walking. To evaluate our SF-BWS robot, we performed a force-tracking and split-force control task using different simulated load weight setups (40, 50, and 60 kg masses). The split-force control task, providing independent force references to each PAM and conducted with a 60 kg mass and a test bench, demonstrates that our SF-BWS robot is capable of shifting human body weight in the mediolateral direction. The SF-BWS robot successfully controlled the two PAMs to generate the desired vertical support forces.

A Review and Comparison of Linear Pneumatic Artificial Muscles

A Review and Comparison of Linear Pneumatic Artificial Muscles

Equivalent-input-disturbance rejection-based adaptive motion control for pneumatic artificial muscle arms via hysteresis compensation models

With outstanding flexibility, pneumatic artificial muscles (PAMs) have shown unique advantages in human–robot interaction environments. However, asymmetric hysteresis nonlinearities, unknown transient or persistent time-varying disturbances, etc., seriously degrade control performance/robustness of PAM arms, and increase actuation failure risks. Meanwhile, existing disturbance rejection methods either rarely handle matched/unmatched disturbances, or require known disturbance dynamics. These defects limit the disturbance rejection ability in practical applications. To this end, a new adaptive output feedback control method is proposed in this article, which achieves efficient positioning and tracking control of PAM arms. Without requiring a priori knowledge of inverse plant models and disturbance upper bounds, the proposed method further enhances robustness against uncertainties and disturbances. Specifically, a generalized Bouc–Wen hysteresis loop is used to describe the asymmetric dynamic force of PAMs. Also, a new adaptive law is designed to compensate for the linearized parameters online. In particular, by applying a modified state observer to derive the equivalent-input-disturbance estimation solution, this article firstly realizes state observation, parameter estimation, and unknown transient/persistent external disturbance rejection simultaneously. The rigorous stability analysis demonstrates that the tracking errors converge to small neighborhoods of the origins. Finally, hardware experimental results with comparisons validate the effectiveness and robustness superiority of the proposed method.

Neural network based patient recovery estimation of a PAM-based rehabilitation robot

Rehabilitation robots have shown a promise in aiding patient recovery by supporting them in repetitive, systematic training sessions. A critical factor in the success of such training is the patient’s recovery progress, which can guide suitable treatment plans and reduce recovery time. In this study, a neural network-based approach is proposed to estimate the patient’s recovery, which can aid in the development of an assist-as-needed training strategy for the gait training system. Experimental results show that the proposed method can accurately estimate the external torques generated by the patient to determine their recovery. The estimated patient recovery is used for an impedance control of a 2-DOF robotic orthosis powered by pneumatic artificial muscles, which improves the robot joint compliance coefficients and makes the patient more comfortable and confident during rehabilitation exercises.

Characteristics verification of pneumatic artificial muscles for compressive loading

A McKibben pneumatic actuator (MPA) is an artificial muscle. Many studies have attempted to investigate the tension exerted by the MPA. However, the MPA also exerts a pushing force when it is compressed. The MPA pushing force affects the motion of robots driven by the MPAs. Therefore, this study aimed to verify the characteristics of the MPA for a compressive load. Knowledge of the compression characteristics can be applied to the motion analysis and modeling of the MPA, and the utilization of the MPA as a structural material. First, a compression test was developed. A compression test of the MPA was conducted to verify the relationship among the input pressure, MPA length, and pushing force. In addition, the deformation mode was measured using the captured images. The pushing force does not monotonically increase with the strain because it deforms in the bending direction. The deformation mode and pushing force differ depending on the end condition. Furthermore, the hysteresis of the MPA and the effects of variations in its characteristics were discussed.

A novel wearable pouch-type pneumatic artificial muscle with contraction and force sensing

In this study, a novel pouch-type pneumatic artificial muscle for wearable applications with a high contraction ratio was proposed. It utilizes a rotary plate-belt mechanism to transfer the expansion of the folded pouch into the contraction of the belt. Modular design of the actuation unit enhances the adaptivity to multiple application scenarios. Based on the principle of virtual work, a force-contraction model considering energy loss was established and verified experimentally. Test results indicate that the actuation unit can attain a contraction force of 35.3 N and contraction ratio of 49.27 %. Moreover, self-contained displacement and force sensing were designed, calibrated, and validated for this actuator. The good displacement tracking and force monitoring performance in the primary feedback control test proved the effectiveness of the self-sensing methods. Finally, surface electromyography (sEMG) of biceps brachii with actuator revealed that muscle activation could be reduced by 30.72 % and 41.27 % without and with 3 kg load, respectively.

Application of Noncircular Pulleys to Straight-Fiber-Type Pneumatic Artificial Muscle Manipulator

This study proposes a method for improving the performance of a manipulator driven by pneumatic artificial muscles. Although the straight-fiber-type pneumatic artificial muscle (SF-PAM), a kind of pneumatic artificial muscle, is lightweight and exhibits high contractile force and contraction percentage, its contractile force decreases as contraction increases. To compensate for the decrease in the SF-PAM contractile force, we developed a noncircular pulley and integrated it into the manipulator driven by a wire pulley mechanism. Because this noncircular pulley is designed in accordance with the output characteristics of SF-PAM, the contraction force of SF-PAM can be converted into manipulator torque efficiently. In addition, the radius of the noncircular pulley is expressed as a function, which can be incorporated into a numerical model for the manipulator’s controller. Subsequently, simulation and experimentation to verify the proposed method showed that, when using the same actuator, the manipulator with a noncircular pulley can optimize both output torque and range of motion better than that with a conventional circular pulley. However, a few differences between simulation results and experimental results were observed. These differences were caused by SF-PAM stretching which was not considered in the model. This drawback can be overcome by improving the SF-PAM and the numerical model in future studies. We believe that this study will provide designers of robots that coexist with humans with a high degree of freedom.

A Study of Energy-Efficient and Optimal Locomotion in a Pneumatic Artificial Muscle-Driven Snake Robot

This paper presents a study of energy efficiency and kinematic-based optimal design locomotion of a pneumatic artificial muscle (PAM)-driven snake-like robot. Although snake-like robots have several advantages over wheeled and track-wheeled mobile robots, their low energy-locomotion has limited their applications in long-range and outdoor fields. This work continues our previous efforts in designing and prototyping a muscle-driven snake-like robot to address their low energy efficiency limitation. An electro-pneumatic control hardware was developed to control the robot’s locomotion and a control algorithm for generating the lateral undulation gait. The energy efficiency of a single muscle (i.e., PAM), a single 2-link module of the robot, and a 6-link snake robot were also studied. Moreover, the power consumption was derived for the snake locomotion to determine the cost of transportation as the index for measuring the performance of the robot. Finally, the performance of the robot was analyzed and compared to similar models. Our analysis showed that the power consumption efficiency for our robot is 0.21, which is comparable to the reported range of 0.016–0.32 from other robots. In addition, the cost of transportation for our robot was determined to be 0.19 compared to the range of 0.01–0.75 reported for the other mobile robots. Finally, the range of motion for the joints of the robot is ±30∘, which is comparable to the reported range of motion of other snake-like robots, i.e., 25∘–45∘.