The performanceof previous machine learning models for gait phase is only satisfactory under limited conditions. First, they produce accurate estimations only when the ground truth of the gait phase (of the target subject) is known. In contrast, when the ground truth of a target subject is not used to train an algorithm, the estimation error noticeably increases. Expensive equipment is required to precisely measure the ground truth of the gait phase. Thus, previous methods have practical shortcoming when they are optimized for individual users. To address this problem, this study introduces an unsupervised domain adaptation technique for estimation without the true gait phase of the target subject. Specifically, a domain-adversarial neural network was modified to perform regression on continuous gait phases. Second, the accuracy of previous models can be degraded by variations in stride time. To address this problem, this study developed an adaptive window method that actively considers changes in stride time. This model considerably reduces estimation errors for walking and running motions. Finally, this study proposed a new method to select the optimal source subject (among several subjects) by defining the similarity between sequential embedding features.

In this paper, we propose a new compact variable gravity compensation mechanism (CVGC). The CVGC can be used to generate gravity compensation torque by using the cam and lever mechanism and can also amplify the target gravity compensation torque by varying the pivot point of the lever. The feature of variable gravity compensation is very useful to the mobile platform, which needs to handle unstandardized tasks with a high variation of the workpiece weight. The proposed CVGC has many advantages. Most importantly, it is designed as a compact, independent one-piece structure and is lightweight, meaning it can easily be used as a mobile platform with a simple modification. The CVGC can also have a full range of compensation angle (360°), so it does not restrict any of the original workspaces of the target platform when it is installed. First, the mechanism concept and details are explained. Next, the mechanics of the prototype for force analysis are presented. Based on these mechanics and cam theory, the methodology of the cam profile design is presented. Finally, the performance of variable gravity compensation is verified through experiments that compare the designed and measured gravity compensation torque. The verification test shows adequate performance, as we had hoped, which shows potential for the development of the CVGC.

We present an autonomous and portable hip-only soft exosuit, for augmenting human walking and running that assists hip extension by delivering peak forces of 300N to the user. Different fixed assistance profiles for walking and running were applied based on an online classification algorithm. The approach is based on the biomechanical understanding that the center of mass potential energy fluctuations during walking and running are out of phase. Specifically, we monitor the vertical acceleration with an abdomen-mounted IMU at the moment of maximum hip extension. Validation is demonstrated with six subjects on the treadmill and with eight subjects outdoors. Our results demonstrated a 99.99% accuracy on average over the fourteen participants for various speeds (0.5 - 4m/s), slopes (-10 -20%), treadmill and overground terrain, loaded (13.6 kg) and unloaded, Exo On and Exo Off conditions, and different shoe types. Results from an evaluation outdoors overground on the energetics of eight subjects demonstrated a significant reduction for running when comparing Exo On to No Exo (3.9%) and for walking and running when comparing Exo On to Exo Off (12.2% and 8.2% respectively). This study represents the first demonstration of an autonomous wearable robot reducing the energy cost of running. Significant variation in response across subjects was observed, highlighting further improvements may be possible via assistance profile individualization with human-in-the-Ioop optimization.

Soft exosuits are a new approach for assisting with human locomotion, which applies assistive torques to the wearer through functional apparel. In this paper, we present a new version of autonomous multi-joint soft exosuit for gait assistance, particularly designed for overground walking. The soft exosuit assists with ankle plantarflexion, hip flexion, and hip extension, equally distributing the forces between ankle plantarflexion and hip flexion. A mobile actuation system was developed to generate high assistive forces, and Bowden cables are used to transmit the forces to the exosuit. A sensor harness connects two load cells and three IMU s per leg that are used to measure real-time data for a controller that commands desired force profiles as a function of the walking cycle. In addition, a control adaptation method was developed which adjusts control parameters while walking on irregular surfaces. In preliminary studies, the proposed method substantially improved the force consistency while walking over uneven terrain. Specifically, the number of steps where the peak force deviated from the target force decreased from 100 to 57 out of 250 steps, and RMS error on the peak force decreased from 90.0 N to 76.6 N with respect to 300 N target force. Also, a two-subject case study on country-course walking demonstrated the potential of this soft exosuit to improve human energy economy while walking overground.

In this paper, we present a design and control approach of a modular off-board actuation system with mono-articular hip exosuit, enabling the instantaneous assistive profile modification of magnitude, shape, and timing. The off-board system consists an actuation unit with two degrees of freedom that can transmit forces to our soft exosuit via Bowden cables. To perform accurate force tracking and cable slack management, we implemented a switching admittance-position control approach that utilizes the advantages of both admittance and position control. In particular, feedforward models (FFMs) are added to the admittance control to compensate variability of individual kinematics, nonlinear hip exosuit stiffness and actuator transmission loss to enable a more accurate force tracking. This system allows us to track force profiles accurately and robustly under normal walking or jogging speed. The performance of force tracking was evaluated on three subjects walking on a treadmill at 1.25 m/s with various magnitude, shape, and timings of assistive profiles and jogging on a treadmill at 2.3 m/s with varied magnitude of a representative assistance profile. Results showed that assistance could be delivered reliably across different profiles. In case of walking experiments, the errors of the magnitude, RMS-E, and timing were within 2.0 N, 8.4 N, and 1.8% when varying the magnitude, shape, and timing respectively. In case of jogging experiments, the RMS-E was within 3.0 N. This system will be used for future research examining how to individualize assistive profiles for different wearers during walking and jogging.

This paper presents a novel haptic device, named VirtuaPower, having abilities of 6 degrees of freedom (DOF) position measurement with a high-force display capability and wide workspace. The VirtuaPower is designed as a parallel mechanism with double in-parallel supporting chains. The mechanical design is presented with constraints and space Jacobians. The workspace and force display capability are computed via kinematic analysis. The VirtuaPower has a wide workspace up to 1 m3 (semicylinder, diameter 1.8 m × height 1.0 m). Moreover, the force display capability is enhanced compared to any existing haptic device, i.e., approximately 100 N of linear force and 10 Nm of torque. The force display ability is validated by an experiment with a 6 DOF force/torque sensor. Finally, a simple virtual reality environment is experientially realized with the VirtuaPower to show its utility as a haptic device.

This paper covers the energy-saving features of a robotics system by redundant actuation. By installing more actuators than the degrees of freedom, the actuating torques can be distributed This distribution can reduce the overall energy loss, which reduces the overall energy consumption. An experiment was conducted with a 2-DOF general manipulator and redundant actuated manipulator; these were made to follow a typical welding pathway used in an automotive factory. The results showed that the redundant manipulator saved up to 38% electrical energy for actuation compared to the general manipulator.

Transitioning capability and high payload capacity are problems for climbing robots. To increase the possible applications for climbing robots, these two abilities are required. We present a new climbing robotic platform named “Combot” to achieve both transitioning capability and high payload capacity. The robot is composed of three main modules with flexible magnetic treads, connecting links with torsion springs and torque-controlled motors, and an active tail at the end of the robot. The robot can perform internal and external transitions using compliant torques from the torsion springs and the active tail. The compliant torques are changed according to external structures; thus, a complex feedback controller is not required. The payload capacity of the robot is measured by 10 kg (1.56 times the robot mass) during flat surface vertical climbing. The robot is expected to be used to move heavy materials to high places in the ship building industry.