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Pulsatile flow is widespread in nature, but replicating such impulsive periodic pumping routines with traditional rotary actuators is complex and energetically inefficient. We demonstrate the feasibility of an actuator capable of generating impulsive flow displacement by exploiting the bistable equilibrium of a simple mechanism. These kind of mechanisms, commonly known as snap-through mechanisms, offer the benefit of sudden release of elastic energy at the interface between two stable structural configurations. This property has been employed in certain actuators to drive abrupt motions of mechanical systems. Here, we use this principle to drive an inflation/deflation routine of a fluid-filled cavity, thus generating a peaked, pulsatile flow, comparable to that encountered in biological systems. Assessment of the various stages of actuation of this system shows that a sharp drop in the energy occurs from elastic to hydraulic work, highlighting the need for improved design elements involved in this stage of the actuation.

In this paper, a swimming robot capable of rapid turns not only horizontally but also vertically in an underwater environment is proposed. The robot utilizes a wire-driven continuum water jet nozzle, which can be oriented in an arbitrary direction and allows the robot to turn in a small radius. In this study, the deformation characteristics of the nozzle were first experimentally investigated, and the nozzle was then implemented in the robot. The performance of the robot was experimentally investigated in an underwater environment. The results indicated that it was capable of a high angular velocity, and could accomplish 180 degree turns within a tactical diameter that was smaller than its body length.

In this paper, an approach toward system theory for soft robotics is considered. An overview of a theoretical scenario is presented by focusing on an elastic rod which is regarded as one of the most essential objects for soft mechanical elements of soft robots. The presented topics include geometry of its backbone curve, kinematics, shape, mechanics (mainly its statics), and discretization, with emphasizing on some important system properties of an elastic rod which will be useful for shape computation and stiffness identification.

We propose a new wearable device for human joint impedance estimation. The device utilizes snap-through buckling of closed-elastica to impose perturbations on human joints. Actuation is based on the law of momentum conservation, that is, the proposed device induces an impact on human joint dynamics. The snap-through buckling generates a comparatively high velocity even with small actuators, and thus, the device is significantly lighter in weight and more compact compared to conventional systems. In addition, it can impose a torque perturbation on a human joint within a sufficiently short time period. Because of the perturbation in the short period, the estimation algorithm also developed in this letter enables us to consider the resulting response as an impulse response, and thereby no synchronization between the input–output data is required. We conduct pilot tests to verify the proposed method for ankle joint impedance estimation and discuss the basic performance of this method compared to the related work. We also discuss the viability of using this method for a variety of purposes in human joint impedance estimation.

Herein we present the development of a novel Ankle Foot Orthosis for gait support of people with foot-drop symptoms. The developed AFO uses an elastic link mechanism to brake the ankle joint during initial contact, thus mitigating foot-slap, and an integrated energy store-and-release mechanism to support toe lift in the swing phase, thus mitigating toe-drag. This paper presents improvements in the braking-holding power of the elastic link mechanism over its previous version, the torque-angle characteristics of the developed AFO with the renewed elastic link, and a pilot test with one person with foot-drop symptoms to verify the proposed functions of the developed AFO.

A human joint impedance estimation method employing a wearable device using the snap-through buckling of closed-elastica has been proposed in our previous study and tested for the ankle joint. In the present study, the method is applied to the wrist impedance estimation scheme. Our method aims at the task-dependent scenarios. The wrist joint is involved in a variety of tasks, where the impedance plays a key role in physical interaction with environments. Because of the unique design and actuation concept, the proposed device does not disrupt the voluntary movements of the wrist and can be used in the estimation during the user’s own motion planning. In this paper, to verify our method, the wrist impedance under the quasi-stationary condition is estimated, and the results are compared with the related works. Also, we discuss the profiles of the induced impulse responses and suggest an alternative estimation manner which does not require any force (torque) information.

Wearable robots suffer from issues of usability, cost-performance, and battery life. These drawbacks hinder the development of their market and their implementation in healthcare and industry. Back support exoskeletons in particular rely heavily on mechanical storing of energy but are still mostly using traditional mechanical elements and actuators to achieve the task. The core technology of our work, named MRLink, uses a smart fluid in combination with a compression spring to produce a unique energy store-and-release functionality. With only 5 Watts MRLink can produce over 500N of braking force. The braking force, variable viscosity, can be continuously controlled through the supply current. With appropriate selection of the spring and control method, the required assist energy can be acquired from body weight and movement dynamics, stored momentarily and, released at the appropriate timing to assist the body motion. The MRLink does not require an external power source like pneumatic actuators, does not require gearboxes and large batteries like DC motors, and comes in a compact package. Thus, this technology has the potential to significantly contribute to wearable exoskeletons in general, and back support exoskeletons in particular. In this work we present the development of a back support exoskeleton prototype based on MRLink, we describe its functional details, and a pilot test partially verifying the proposed functions.

In this study, a simulation of a real-time surface undulation detection system based on machine learning techniques was developed. In this system, surface undulations are sensed using a sensor called the “strain-gauge-sandwiched rubber artificial skin layer,” and the digitized undulation data are processed by fast Fourier transform and input into a single-layer neural network. Preliminary results suggest that the proposed system is capable of discriminating convex deformations ranging from 0 to 60 μm in height.

In this paper, we study a compact wheeled robot that can jump while rolling. Some robots are capable of jumping or rolling, but as far as we know, those robots are not focused on jumping while rolling. We know that animals jump while running to escape from predators. Robots can move quickly by jumping while rolling. We consider a model of a robot jumping while rolling and evaluate the proposed robot. The proposed robot has two wheels and a jumping mechanism based on snap-through buckling of an elastic strip. The proposed robot can jump about 5.9 cm high and 22 cm wide on average while maintaining a traveling speed of about 1.2 m/s. The proposed robot can change the jumping angle without greatly decreasing the impulse for the moving speed.

In this paper, we proposed a model for a wire-driven continuum manipulator without assuming constancy in curvatures of the manipulator's shape as a natural extension of the famous and useful constant curvature model. We show that the tip orientation of the continuum manipulator can be decided completely by pulling-wire lengths, regardless of its whole shape, which is a useful property same as the constant curvature model. Moreover, we can derive the tip position, which depends on the whole shape, by assuming distributed forces along wires mainly due to the friction between the wires and their surrounding materials. Experimental validation results show that, based on the model, we can estimate the tip orientation from pulling-wire lengths with good accuracy and precision. We also provide experimental results for discussion about estimating the tip position with the realistic assumption on the force distribution along wires.

The paper provides reasonable determination of the mapping rule and the sampling interval for human joint impedance estimation based on the observation from a variety of viewpoints. While a human joint can be modeled by a linear second-order continuous-time system, conventional parametric estimation methods such as the least squares method is carried out with the sampled input-output data, and thus, the obtained results belong to a difference model. In the paper, using the mapping model, the algebraic relationship transforming the difference model to the continuous-time model is derived with remaining a parameter to determine the mapping rule. This enables us to evaluate the effect of the determination of the mapping rule with the selected sampling interval, and the paper shows an example of the human ankle case. Although other examples are not shown here, based on the discussion, the determination provided by the paper can be utilized for other cases to estimate the human joint impedance by the parametric estimation methods.

In this paper, we propose a real-time spatial shape estimation method for an elastic rod. Our proposed method does not use any image sensor nor shape sensor, but does use a six-axis force/torque sensor placed near one end of the elastic rod. In the proposed shape estimation method, the occlusion problem never occurs principally because the shape of a flexible object will be estimated based on an elastic rod model. We utilize the discretized Kirchhoff elastic rod for shape estimation, which can be viewed as a serial chain of rigid bodies connected with three-degree-of-freedom rotational spring joints. We show that real-time spatial shape estimation is possible based on real-time sensing of force/torque information. The computational time of the proposed shape estimation algorithm is linear in the number of rigid-body partition. Moreover, the required calculations are very simple owing to deep understanding of robot manipulator kinematics. Thus we can compute the spatial rod shape in realtime. We show experimental results in order to validate our proposed method.