Fabric muscle with a cooling acceleration structure for upper limb assistance soft exosuits.

Soft exosuits used for supporting human muscle strength must be lightweight and wearable. Shape memory alloy (SMA) spring-based fabric muscles (SFM) are light and flexible, making them suitable for soft and shape-conformable exosuits. However, SFMs have a slow actuation speed owing to the slow cooling rate of the SMA spring. This paper proposes a forced air-cooling fan-integrated fabric muscle (FCFM) that improves the cooling rate by arranging a thin-diameter SMA spring bundle with a high surface-area-to-volume ratio inside a breathable fabric with integrated fans. The relaxation time of an FCFM weighing 30 g and containing a 2.6 g SMA spring bundle, which contains 200 thin springs, was reduced by over 70.2% via forced-air cooling using the integrated fans. A 4 kg weight, which is 1530 times the mass of the SMA spring bundle, was hung from the FCFM and was repeatedly actuated in ten-second cycles. An upper limb assistive soft exosuit with FCFMs was fabricated and worn on a mannequin holding a dumbbell, and the arm extension time after flexion was improved by 4.5 times. Additionally, the assistive performance of the exosuits for repetitive tasks in specific scenarios was evaluated, and the strong potential of the proposed FCFM for soft exosuits was verified.

Rugged and Compact Three-Axis Force/Torque Sensor for Wearable Robots.

In the field of robotics, sensors are crucial in enabling the interaction between robots and their users. To ensure this interaction, sensors mainly measure the user's strength, and based on this, wearable robots are controlled. In this paper, we propose a novel three-axis force/torque sensor for wearable robots that is compact and has a high load capacity. The bolt and nut combination of the proposed sensor is designed to measure high-load weights, and the simple structure of this combination allows the sensor to be compact and light. Additionally, to measure the three-axis force/torque, we design three capacitance-sensing cells. These cells are arranged in parallel to measure the difference in capacitance between the positive and negative electrodes. From the capacitance change measured by these sensing cells, force/torque information is converted through deep neural network calibration. The sensing point can also be confirmed using the geometric and kinematic relation of the sensor. The proposed sensor is manufactured through a simple and inexpensive process using cheap and simply structured components. The performance of the sensor, such as its repeatability and capacity, is evaluated using several experimental setups. In addition, the sensor is applied to a wearable robot to measure the force of an artificial muscle.

Soft Inductive Coil Spring Strain Sensor Integrated with SMA Spring Bundle Actuator.

This study proposes a soft inductive coil spring (SICS) strain sensor that can measure the strain of soft actuators. The SICS sensor, produced by transforming a shape memory alloy (SMA) wire with the same materials as that of an SMA spring bundle actuator (SSBA) into a coil spring shape, measures inductance changes according to length changes. This study also proposes a manufacturing method, output characteristics of the SICS sensor applicable to the SSBA among soft actuators, and the structure of the SICS sensor-integrated SSBA (SI-SSBA). In the SI-SSBA, the SMA spring bundle and SICS sensor have structures corresponding to the muscle fiber and spindle of the skeletal muscle, respectively. It is demonstrated that when a robotic arm with one degree of freedom is operated by attaching two SI-SSBAs in an antagonistic structure, the displacement of the SSBA can be measured using the proposed strain sensor. The output characteristics of the SICS sensor for the driving speed of the robotic arm were evaluated, and it was experimentally proven that the strain of the SSBA can be stably measured in water under a temperature change of 54 °C from 36 to 90 °C.

A Novel Fabric Muscle Based on Shape Memory Alloy Springs.

Fabric muscle is important for wearable robots that are soft, compliant, and silent with high contractility and high force. This study presents a novel shape memory alloy (SMA) spring-based fabric muscle (SFM). The SFM is manufactured by bundling SMA springs with proven performance as artificial muscle. The SFM generates high contractility and high force, and is soft, flexible, and light because it is covered with fabric used to make actual clothes. The SFM is contracted by heat and shows a contraction strain of 50% at a heating temperature of 70°C while generating 100 N force or higher. Furthermore, it generates a maximum contraction strain of 67% under no load. To drive it with the optimum voltage and current, the SFM is designed by optimizing the serial and parallel connection methods for the embedded SMA springs. We propose herein design and manufacturing methods for the SFM and verify the usability of the SFM as a soft actuator through a performance evaluation. The SFM as a soft actuator with a simple structure-like fabric is easily applicable to soft wearable robots that can support muscle power by simply being attached to usual suits. The SFM has a soft touch, and is lightweight; hence, it has the potential for wide applications to new-concept soft wearable robots that can be comfortably worn anytime and anywhere like usual clothes.

Suit-type Wearable Robot Powered by Shape-memory-alloy-based Fabric Muscle.

A suit-type wearable robot (STWR) is a new type of soft wearable robot (SWR) that can be worn easily anywhere and anytime to assist the muscular strength of wearers because it can be worn like normal clothes and is comfortable to wear even with no power supply. This paper proposes an STWR, in which a shape-memory-alloy-based fabric muscle (SFM) is used as the actuator. The STWR, which weighs less than 1 kg, has a simple structure, with the following components: SFMs, wire encoders for measuring the contraction length of the SFMs, and BOA that fix the actuators on the forearms. In this study, a position controller for the SFM using the wire encoder was developed, and a prototype STWR was fabricated using this position controller. Moreover, by putting the STWR on a mannequin, step-response experiments were performed in which the arms of the mannequin lifted barbells weighing 2 kg and 4 kg to a certain target position. A fast response of moving to the target position in less than 1 s was observed in all steps except for the initial heating step for the 2 kg barbell. The response speed of the SFM was noticeably slower for the 4 kg barbell compared to that for the 2 kg barbell; it moved to the target position in approximately 3 s in all the steps except for the initial heating step. The SFM-applied STWR could overcome the limitations of conventional robots in terms of weight and inconvenience, thereby demonstrating the application potential of STWRs.

Note: Radial-thrust combo metal mesh foil bearing for microturbomachinery.

This Note proposes a novel radial-thrust combo metal mesh foil bearing (MMFB). Although MMFBs have advantages such as higher stiffness and damping over conventional air foil bearings, studies related to MMFBs have been limited to radial MMFBs. The novel combo MMFB is composed of a radial top foil, thrust top foils, and a ring-shaped metal mesh damper--fabricated by compressing a copper wire mesh--with metal mesh thrust pads for the thrust bearing at both side faces. In this study, the combo MMFB was fabricated in half-split type to support the rotor for a micro gas turbine generator. The manufacture and assembly process for the half-split-type combo MMFB is presented. In addition, to verify the proposed combo MMFB, motoring test results up to 250,000 rpm and axial displacements as a function of rotational speed are presented.

Vacuum chamber-free centrifuge with magnetic bearings.

Centrifuges are devices that separate particles of different densities and sizes through the application of a centrifugal force. If a centrifuge could be operated under atmospheric conditions, all vacuum-related components such as the vacuum chamber, vacuum pump, diffusion pump, and sealing could be removed from a conventional centrifuge system. The design and manufacturing procedure for centrifuges could then be greatly simplified to facilitate the production of lightweight centrifuge systems of smaller volume. Furthermore, the maintenance costs incurred owing to wear and tear due to conventional ball bearings would be eliminated. In this study, we describe a novel vacuum chamber-free centrifuge supported by magnetic bearings. We demonstrate the feasibility of the vacuum chamber-free centrifuge by presenting experimental results that verify its high-speed support capability and motoring power capacity.

Complexity-reduced scheme for feature extraction with linear discriminant analysis.

Owing to the singularity of the within-class scatter, linear discriminant analysis (LDA) becomes ill-posed for small sample size (SSS) problems. Null-space-based LDA (NLDA), which is an extension of LDA, provides good discriminant performances for SSS problems. Yet, as the original scheme for the feature extractor (FE) of NLDA suffers from a complexity burden, a few modified schemes have since been proposed for complexity reduction. In this brief, by transforming the problem of finding the FE of NLDA into a linear equation problem, a novel scheme is derived, offering a further reduction of the complexity.

Identification of finite state automata with a class of recurrent neural networks.

A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The application of the proposed network is addressed in the encoding, identification, and extraction of finite state automata (FSAs). Simulation results show that the identification of FSAs using the proposed network, trained by the hybrid greedy simulated annealing with a modified cost function in the training stage, generally exhibits better performance than the conventional identification procedures.

Note: Development of a small maglev-type antirolling system.

Various passive and/or active antirolling devices have been used for suppressing the rolling motion of ships in the ocean. In this study, a maglev-type active mass driver (AMD) is developed for controlling the rolling motion of a shiplike structure. No friction is generated during the motion of this maglev-type AMD, as the moving mass is floated by the magnetic levitation force and displaced by the propulsion force generated by the linear motor. For verifying the feasibility of the proposed method, a small AMD having a moving mass of approximately 4.0 kg is constructed and used in a small-scale model of a catamaran. This paper presents the detailed design procedures and obtained experimental results. Our results show that the developed maglev-type AMD has the potential for use in controlling the rolling motion of ships and other oceanographic vessels.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.