可変剛性機構を用いたロボット膝装具の開発と実験的評価

This paper presents a compact variable stiffness mechanism (VSM) with reconfigurability. The VSM is able to achieve variable stiffness in adjustable ranges, due to its reconfigurable design. The new VSM features with a compact and light weight structure, and can be used as a stand alone module, or integrated in wearable elbow exoskeletons and other transmissions. In the paper, mechanics models are developed for VSM to reveal the stiffness performance and torque-deflection characteristics. A prototype of VSM is constructed and static testing results validate the models. The proposed VSM is finally integrated in a wearable elbow exoskeleton.

A wide-range variable stiffness mechanism for semi-active vibration systems

In this paper, a novel variable stiffness mechanism (VSM) based on specially designed S-springs made from shape memory alloy (SMA) is developed. Based on the stiffness model, by changing the state combination of the SMA S-springs with different thicknesses, the actuator's stiffness can be discretely adjusted online. The stiffness adjustment range of the actuator can be conveniently extended almost from 0 N/m to infinity by changing the preset spring angle manually offline without a complex mechanical mechanism or replacing any parts. A linear digital variable stiffness actuator (LDVSA) is also designed with the VSM. Some tests of the SMA S-springs, as well as the actuator's stiffness under different configurations, comparisons with other actuators and its trajectory tracking capacity are conducted to verify its design. Then, a dynamic model of the actuator is established and its bandwidth is analysed. Based on this, explosive experiments are designed and performed to explore the application potential of the actuator. Experimental results are provided to illustrate the explosive capacity and energy efficiency of the proposed design.

Soft robots have advantages such as low weight and compact size compared to rigid robots. Variable stiffness is one of the key methods of improving the performance of a soft robot. The soft gripper grasps objects of various shapes or sizes based on the variable stiffness. In a previous study, we validated the variable stiffness mechanism where flexible and rigid segments were connected alternately in series. This paper presents a soft variable stiffness gripper that can be used to control the stiffness by pulling tendons. The soft gripper has three variable stiffness structures acting as fingers and the stiffness can be controlled using two motors by winding tendons. To understand the tendency of the stiffness variation and determine the design parameters, a compliant mechanism was developed using a pseudo-rigid-body model (PRBM). The experimental results show that the difference between the lowest and highest stiffness values of the fabricated variable stiffness gripper was 5.6 times the original. Similarly, the difference in the gripping weight was 19 times. Using the experimental results, the variable stiffness gripper can be designed and manufactured based on the required stiffness and used to grip various types of objects.

Wearable robots, especially power suits to enhance human activity are one of most interesting topics. This study aims to develop a power suit installing a variable stiffness mechanism. In a previous study, we showed that the relation between impedance parameters of power suits and human performance, and verified the effectiveness of self impedance matching method using soft computing. In this paper, we conduct fundamental experiments in order to design a variable stiffness mechanism, which can tune the stiffness of joint mechanically. Experimental results show the effectiveness of variable stiffness for improving human performance and reducting muscle fatigue. Moreover, we try to design the variable stiffness mechanism, and to verify the effectiveness by simulation.

Segment-interaction and its relevance to the control of movement during sprinting

Configuration synthesis of variable stiffness mechanisms based on guide-bar mechanisms with length-adjustable links

Human lower limbs have particular flexibility. Both the efficiency of bipedal walking and the ability to protect actuators with low energy loss are worthy references for the design of bipedal robots. This paper proposes a design for a biped robot with joints of variable stiffness. The robot has three degrees of freedom in the sagittal plane in each leg. The hips and knees are driven directly by the motor, while the ankles are passive joints with adjustable stiffness. After a comprehensive investigation, a variable stiffness mechanism was introduced based on lever principles, and driven by a motor that can realize real-time adjustment. Simulations verified the necessity of variable stiffness joints in the robot. The variable stiffness joint can absorb the ground impact on each joint, reduce the energy loss of the motor, and improve the efficiency of movement.

Human walking is an important and intuitive operation in daily life, but it is different for people missing this ability. Recognizing human gait cycle portions during walking is very useful for understanding the biomechanics of the muscles, pre-disease’s diagnosis, and designing lower limb prosthetics. The normal gait cycle is divided into stance and swing phases. In this work, benchmarking of several classification techniques is performed, based on electromyography (EMG) data collected from seven lower limb muscles, with the gait cycle phase used as a target vector to label the EMG data. The dataset is split into a training set used to build a statistical model using a specified classification technique, and a test set for purpose of testing a pre-generated statistical model. EMG signals are unfortunately normally corrupted with noise, which drastically reduces their classification performance. A median filter and root mean square (RMS) filter were thus applied to the raw EMG signals, and the performance of the classification techniques calculated in all cases for the raw EMG, EMG with median filter, and EMG with RMS filters for comparison purposes. The use of filters offered good enhancement in the classification process. The median filtered EMG signal performed best and gave higher accuracy than the raw EMG and RMS filtered EMG signals due to the technique’s efficacy in removing outliers. This work also offers a simple explanation of each classifier algorithm used, and a graphical feature selection was also applied to all seven muscles of interest to identify the muscle with the most influence on the gait cycle. The Rectus Femoris muscle shows the best activity separation between swing and stance phases, working mainly during the swing phase; this higher activity during the swing phase thus caused it to be identified as the muscle with the most influence over the normal gait cycle.

Designing robotic systems capable of low-power operation, inherent to their compliant actuation, has been elusive in practical application. In this paper, we propose a physical measure to mathematically define mechanical designs that are suitable to realize stiffness modulation with low power cost. Using this measure, we present a mathematical formulation of an ideal variable stiffness mechanism unaffected by the external load during its operation. We then analyze several existing mechanisms from the literature to relate design features with analytical conditions inherent to low power stiffness modulation in practical designs. Through this analysis, we identify an approximate practical realization of an ideal actuator capable of stiffness modulation with inherently low power cost. Similar to a number of existing efficient variable stiffness mechanisms, this mechanism is able to hold a given stiffness setting with zero input force under no external load. However, unlike many other previously designed mechanisms, it enables infinite range stiffness modulation using finite control forces. A practical variable stiffness mechanism that is capable of infinite range stiffness modulation using finite control forces leads to lower power cost and reduced energy consumption.

Low-cost variable stiffness joint design using translational variable radius pulleys

The complex construction of the joint apparatus of the cat distal forelimb, which allows the paw three degrees of freedom, poses special requirements on the neural signals controlling the paw position. To understand the electromyography (emg) signals of the distal forelimb muscles during locomotion, it is necessary to know the kinematics of the forelimb joints in detail. As no such information is available, we used the pulsed X-ray technique in trained cats during treadmill locomotion to analyse the angular excursions of the wrist, the metacarpophalangeal (MCP) and the proximal interphalangeal (PIP) joints. X-ray illuminations were done in either the parasagittal or the frontal plane. At the beginning of the stance phase the wrist (WR) and the MCP joints extended slowly, and the PIP joints flexed. Whereas the WR and the PIP joints maintained a constant angular position of approximately 200 degrees and 60 degrees, respectively, throughout the stance phase, extension continued in the MCP joints from 240 degrees at touch-down to 300 degrees at the end of the stance phase. Slightly before lift-off (100 ms) the WR and the MCP joints flexed rapidly. This flexion changed approximately 150 ms after lift-off into a slow extension. The PIP joints extended rapidly at the beginning and at the end of the swing phase, during the interposed period of the swing phase they displayed a slow flexion. Rotatory movements of the forelimb in the radioulnar joints were present during the swing and stance phases. During the swing phase the limb first supinated (starting 100 ms after lift-off); pronation occurred immediately before ground contact. During the stance phase the supination angle was kept constant until 100 ms before lift-off, when a short pronation was found. The paw was kept in an ulnar deviated position throughout the complete step cycle. Ulnar deviation decreased at the end of the swing and stance phases. The results of this study increase our understanding of how the body weight is transmitted on to the ground. They suggest four main functions for the skeletomotor apparatus and the underlying neural commands to secure the forward movement of the animal during the stance phase: (i) preparation and stabilization of a force-transmitting platform; (ii) stabilization of the wrist and the carpal/metacarpal joints; (iii) stabilization of the supination angle; (iv) antigravity control of the extension in the MCP.

Kinematic Features of Rear-Foot Motion Using Anterior and Posterior Ankle-Foot Orthoses in Stroke Patients With Hemiplegic Gait

The main objective of this work is to make an algorithm to detect onset and offset of stance and swing phase of human gait cycle. In order to proceed, the signal from the force sensors (placed underneath each foot) were first divided according to the fundamental period by auto-correlation. This ensures that each period contains a full stance phase and two fragmented swing phases. After this step, Short Time Fourier transform has been performed on each period of the signal to detect the initial search point (highest DC value) on the stance phase. Then by judging the width and slope of the straight line from changing search points on the signal to a changing destination point (starting from the minimum or maximum time value) of the graph the onset and offset of the stance and swing phase has been detected. The changing search point has small distance from the previous one, if the slope of the signal is small, but the distance increases with the increasing change of slope of the signal. The destination point changes with the change of slope of the straight line. This algorithm has been applied to the signals in the database of Parkinsons disease, which shows a success rate of more than 90%.

Peak medial (but not lateral) hamstring activity is significantly lower during stance phase of running. An EMG investigation using a reduced gravity treadmill