Development of large-scale stacked-type electrostatic actuators for use as artificial muscles

Electrostatic actuators have the advantages of light weight, flexibility, and high energy efficiency, which make them suitable for use as artificial muscles. However, a traditional electrostatic actuator cannot generate long strokes and a high force density at the same time because such actuator would excessively widen the gap between the electrodes because of its structure. This paper presents a newly developed large-scale stacked-type electrostatic actuator (LSEA) intended for use as an artificial muscle for robots. LSEA is a multi-stacked electrostatic actuator that can be linearly contracted by the application of a voltage. It has a unique structure that prevents overextension of the gap between the electrodes. It can therefore generate a large force. The spring characteristics and the relationship between the contractive force and the stroke were experimentally determined. The findings showed that LSEA prevents the overextension of the gap between the electrodes and has a high contraction ratio that is equivalent to that of a mammalian skeletal muscle.     

Extraction and implementation of muscle synergies in neuro-mechanical control of upper limb movement

This work faces the redundancy problem, a central concern in robotics, in a particular force-producing task by using muscle synergies to simplify the control. We extracted muscle synergies from human electromyograph signals and interpreted the physical meaning of the identified muscle synergies. Based on the human analysis results, we hypothesized a novel control framework that can explain the mechanism of the human motor control. The framework was tested in controlling a pneumatic-driven robotic arm to perform a reaching task. This control method, which uses only two synergies as manipulated variables for driving antagonistic pneumatic artificial muscles to generate desired movements, would be useful to deal with the redundancy problem; thus, suggesting a simple but efficient control for human-like robots to work safely and compliantly with humans.     

一种克服sEMG人机交互中肌肉疲劳的SVM算法

在基于表面肌电信号的人机交互系统中,产生的肌肉疲劳降低了系统的稳定性。针对该问题,分析肌肉正常状态和疲劳状态下的肌电信号变化规律,提出一种改进的在线支持向量机增量训练算法。该算法在每次训练SVM(Support Vector Machine)模型时,计算各样本到分类超平面的距离,并以之为条件对不断更新的训练数据进行有条件的选择和遗忘,只留下最大距离1/2以内的数据。通过在线训练不断更新训练样本来获得新的SVM模型,用于适应肌肉疲劳过程中肌电信号的变化,同时防止多次在线训练过程中更新的样本改变训练集间初始边界。最后在智能轮椅上进行验证,实验结果表明:该算法有效减少了肌肉疲劳在人机交互系统中的影响,使得系统能够保持长时间稳定操作。     

Adaptive robust posture control of a parallel manipulator driven by pneumatic muscles

Rather severe parametric uncertainties and uncertain nonlinearities exist in the dynamic modeling of a parallel manipulator driven by pneumatic muscles. Those uncertainties not only come from the time-varying friction forces and the static force modeling errors of pneumatic muscles but also from the inherent complex nonlinearities and unknown disturbances of the parallel manipulator. In this paper, a discontinuous projection-based adaptive robust control strategy is adopted to compensate for both the parametric uncertainties and uncertain nonlinearities of a three-pneumatic-muscles-driven parallel manipulator to achieve precise posture trajectory tracking control. The resulting controller effectively handles the effects of various parameter variations and the hard-to-model nonlinearities such as the friction forces of the pneumatic muscles. Simulation and experimental results are obtained to illustrate the effectiveness of the proposed adaptive robust controller.     

Large‐Stroke Electrochemical Carbon Nanotube/Graphene Hybrid Yarn Muscles

Artificial muscles are reported in which reduced graphene oxide (rGO) is trapped in the helical corridors of a carbon nanotube (CNT) yarn. When electrochemically driven in aqueous electrolytes, these coiled CNT/rGO yarn muscles can contract by 8.1%, which is over six times that of the previous results for CNT yarn muscles driven in an inorganic electrolyte (1.3%). They can contract to provide a final stress of over 14 MPa, which is about 40 times that of natural muscles. The hybrid yarn muscle shows a unique catch state, in which 95% of the contraction is retained for 1000 s following charging and subsequent disconnection from the power supply. Hence, they are unlike thermal muscles and natural muscles, which need to consume energy to maintain contraction. Additionally, these muscles can be reversibly cycled while lifting heavy loads.     

T–S fuzzy model-based tracking control of a one-dimensional manipulator actuated by pneumatic artificial muscles

Pneumatic artificial muscle (PAM) has highly nonlinear and time-varying behavior due to gas compression and nonlinear elasticity of the bladder containers. Hence, it is difficult to achieve excellent tracking performance when using classical control methods. This study proposes a Takagi–Sugeno (T–S) fuzzy model-based control for improving control performance. The proposed approach decomposes the model of a nonlinear system into a set of linear subsystems. This allows, the T–S fuzzy model-based controller to use simple linear control techniques providing a systematic framework for the design of a state feedback controller. Stability analysis is carried out using Lyapunov direct method. The powerful LMI Toolbox in MATLAB is employed to solve linear matrix inequalities (LMIs) to obtain the controller gains. Experimental results verified that the proposed controller can achieve excellent tracking performance under different disturbances.     

A modified version of the three-compartment model to predict fatigue during submaximal tasks with complex force-time histories

The three-compartment model (3CM) was validated previously for prediction of endurance times by modifying its fatigue and recovery rates. However, endurance times do not typically represent work demands, and it is unknown if the current version of the 3CM is applicable for ergonomics analysis of all occupational tasks. The purpose of this study was to add biological fidelity to the 3CM, and validate the model against a series of submaximal force plateaus. The fatigue and recovery rates were modified to represent graded physiological motor unit characteristics (termed 3CM_GMU). In nine experiments of submaximal efforts, the 3CM_GMU produced a root-mean squared difference (RMSD) of 4.1 ± 0.5% MVC over experiments with an average strength loss (i.e. fatigue) of 31.0 ± 1.1% MVC. The 3CM_GMU model performed poorly for endurance tasks. The 3CM_GMU model is an improvement for evaluating submaximal force patterns consisting of intermittent muscle contractions of the hand and forearm.

Practitioner Summary: We modified an existing fatigue model using known physiological properties in order to predict fatigue during nine different submaximal force profiles; consistent with efforts seen in industrial work. We expect this model to be included in digital human modelling software, for the assessment of repetitive work and muscle fatigue in repetitive tasks.

Social Media Summary: The proposed model has applications for estimating task fatigue in proactive ergonomic analyses of complex force patterns using digital human models.     

Influence of smartphone use styles on typing performance and biomechanical exposure

Twenty-seven subjects completed 2-min typing tasks using four typing styles: right-hand holding/typing (S-thumb) and two-hand typing at three heights (B-low, B-mid and B-high). The styles had significant effects on typing performance, neck and elbow flexion and muscle activities of the right trapezius and several muscles of the right upper limb (p < 0.0001 by repeated-measure analysis of variance). The subjects typed the fewest words (error-adjusted characters per minute: 78) with the S-thumb style. S-thumb style resulted in similar flexion angles of the neck, elbow and wrist, but significantly increased muscle activities in all tested muscles compared with the B-mid style. Holding the phone high or low reduced the flexion angles of the neck and right elbow compared with the B-mid style, but the former styles increased the muscle activity of the right trapezius. Right-hand holding/typing was not a preferable posture due to high muscle activities and slow typing speed.

Practitioner Summary: Right-hand holding/typing was not favoured, due to increased muscle activities and slower typing speed. Holding the phone high or low reduced the flexion angles of the neck and right elbow, but the former styles increased the muscle activity of the right trapezius compared with holding the phone at chest level.     

Effect of local wrist muscle fatigue on multiple assembly‐related psychomotor skills

Human operators are still a vital resource in modern manufacturing systems, especially for fine assembly tasks. Declining muscle strength due to physical tasks can impair psychomotor skills and can cause adverse effects on assembly quality. To understand how local muscle fatigue can influence multiple psychomotor skills, 20 subjects participated in an experiment in which four psychomotor tests were performed to mimic fine assembly tasks, and their performances under nonfatigued wrist and fatigued wrist conditions were compared. Results showed that wrist fatigue caused significant decrements in the dexterity of fingers and fingertips, but there was no significant influence on arm‐hand steadiness. Local muscle fatigue impairs psychomotor skills to different extents but does not necessarily lead to lower performance. Humans are capable of coordinating motion units to compensate for the influence of muscle fatigue, but this is rather limited. It is suggested that in assembly operations, tasks should be arranged according to different task demands on diverse psychomotor skills.     

气动人工肌肉关节的自抗扰控制

气动人工肌肉关节系统是一个强非线性时变自平衡2阶系统,鉴于传统控制方法难以克服控制精度、调节速度和稳定性之间的矛盾,设计了一种2阶自抗扰控制器.采用3阶扩张状态观测器实时估计未建模型部分及外界扰动,对系统进行线性补偿,并利用非线性反馈机制提高控制效率,在保证稳定性的前提下,提高调节速度和控制精度,使得系统的稳态精度小于...