Wearable robots recently become a hopeful technology for support and assist of human activity in many fields. A major issue discussed in this research field to this date is limb mobility of a person wearing a wearable robot. It is considered that the mobility receives influence from factors such as alignment of a wearable robot mechanism on human limbs, control of the robot, mechanical design of the mechanism etc. This paper considers two mechanical designs of the mechanism for motion support of a human elbow joint, and compare those mobility based on relative motion between a human arm and the mechanism, under an assumption that the mechanism does not receive special care for its alignment on a human arm. The comparison of the mobility obtained from measured data of persons wearing the mechanism does not statistically exhibit significant difference between the mechanical designs, however, it also brings up some issues for future study.

The proficiency levels of using chopsticks and/or writing characters with a pencil etc. are improved by the practices continuously repeated. By the way, the mechanisms of improving the proficiency level of human skill have never been clarified. This study focused on the mechanism of our skill acquirement and investigates the change in muscular activity in the process of skill acquirement. This paper describes the experimental device we have developed, where a skilled instructor and a beginner operate the experimental device linked to a simple paddle application. We will investigate the process of human skill acquirement by focusing on the changes in the activities of brachial muscles while training. Especially, the effects of physical instruction of an instructor on the skill acquirement of a beginner will be discussed in this paper.

This paper considers experimental investigation of an antagonistically actuated robot manipulator. The focus of the investigation is how biarticular actuation contributes to control of the manipulator. Based on the feature that antagonistically robot manipulators can be controlled by feedforward control with constant inputs, this paper treats the case of PTP (point-to-point) control of robot postures. Due to expectation of difficulty for analytical approach, this paper takes experimental methodology of acquiring mappings between sensory and motor spaces by ANNs (artificial neural networks). Based on the idea that contribution of biarticular actuation may be influenced by choice of a sensory space, this paper considers not only joint angles of a manipulator but also Cartesian coordinate and angles in binocular visual space at the hand of the manipulator as sensory spaces. For each of them, the mappings obtained from trained ANNs are compared for the cases with and without biarticular actuation, based on interpolation performance of the ANNs examined through PTP control of the manipulator. The results of the comparison shows that choice of a sensory space is less effective to the interpolation performance in the case of biarticular actuation.

This paper is the first report on development of WELL-joint (Wearable ELbow Lightweight joint) for assist of a human elbow. The final goal of the development is realization of a lightweight and compact joint. Two actuators and two nonlinear springs constitute an antagonistic actuation system, and assist of a human elbow is realized by changing stiffness and equilibrium around the joint. This paper reports mechanical design and static analysis of WELL-joint. Experimental results are compared with analytic results for evaluation of control accuracy. Future work is also issued.

A parallel-wire driven mechanism uses flexible wires instead of heavy rigid links. In this paper, we propose a robust point-to-point (PTP) position control method in the task-oriented coordinates for completely restrained parallel wire-driven robots, which are translational systems using the minimum number of wires under zero-gravity conditions. In the cases where parallel-wire driven robots are disassembled/assembled and used outdoors (also applied in space), actuator positions would be uncertain or contain some errors. The error of internal force among wires that results from such uncertainty of actuator positions deteriorates positioning performance. To overcome such a difficulty, adaptive compensation is employed for robust PD control against the error of internal force, in this paper. It is necessary for the adaptive compensation to separate the internal force term linearly into a regressor matrix and a parameter vector concerned with the errors of actuator positions. The internal force term, however, possesses the nonlinear characteristic concerned with the errors of actuator position. Noting the structure of the internal force term, this paper shows that measuring both the position of an end-effector and wire length in real time enables the linear separation. Not only does this robust PD control method ensure precise positioning using external sensors; it enhances the robustness for uncertainty of the Jacobian matrix, which results from the error of actuator installation. First, we explain the linearization of the internal force term. Next, the robust PD control for the parallel-wire driven system using the uncertain Jacobian matrix is proposed; then, we prove the motion convergence to desired points and discuss its robustness based on Lyapunov stability analysis. Finally, the usefulness of the proposed control method is demonstrated through experiments and simulations.

A parallel wire driven mechanism uses flexible wires instead of heavy rigid links. In this paper, we propose an adaptive position control method for the fully constrained parallel wire-driven systems that use the minimum number of wires under zero-gravity conditions. Unfortunately, conventional methods of adaptive control cannot be used directly because of the nonlinearity of an internal force term. To overcome such an impossibility, we incorporate a new idea into the conventional method to separate the internal force term linearly. Not only does this adaptive control method ensure precise positioning using external sensors; it enhances the robustness for uncertainty of the Jacobian matrix, which results from the error of actuator installation. First, we explain the linearization of the internal force term. Next, the adaptive control method for the parallel wire driven system using the uncertain Jacobian matrix is proposed; then we prove the motion convergence to desired points and discuss its robustness based on Lyapunov stability analysis. Finally, the usefulness of the proposed control scheme is demonstrated through both experiments and simulation

The goal of our study is development of a "tactile mirror" for displaying tactile perception information. A point of distinctive difference between a tactile mirror and conventional tactile displays is that a tactile mirror possesses a feedback mechanism for acquiring the contact state information on the finger pad concerning not force but tactile perception sensation. The primary development concerns human static friction sensation. First, a control method and the structure of a tactile mirror are described. Second, simulation results using FEM for contact analysis and a ANN(artificial neural network) for generating feedback signals are shown. Finally, experiments demonstrating that providing a feedback component accomplish accurate display of static friction sensation with a conventional type of tactile displays.

It is considered that kinesthetic feeling induced by the kinetic characteristic of a manipulated object plays an important role for performance of human daily skills. Therefore, if we consider a wearable robot/joint as the robot/joint operated by the daily skills, it is necessary to control the robot/joint so that kinesthetic feeling induced by the kinetic characteristic of an object is directly transmitted to a wearer, without any distortion by the kinetic characteristic of the wearable robot/joint itself. This is the control issue of "kinesthetic transparency". This paper discusses a method of control to improve kinesthetic transparency of a wearable joint. Kinesthetic transparency can be basically improved by active compensation. In order to avoid necessity of offline estimation for unknown kinetic parameters of the joint, this paper formulates a control law which automatically estimates the unknown parameters during operation of the joint. Simulation results demonstrate effectiveness of the method. However, experimental results reveal that accurate compensation of frictional terms is necessary for further improvement.

To successfully incorporate human skills into a wearable robot, it is required to design its joint mechanism so that it does not interfere with the human skills. From this viewpoint, this paper first addresses six design goals for the joint mechanism. Based on the result of preliminary examination for two well-known mechanisms, a new 6-DOF mechanism referred to as the Wearable HEXA mechanism is proposed. This is based on the HEXA, which has been originally developed as a high-speed manipulator. Detail of its design process is given, and evaluation of a trial mechanism manufactured along the design process is also reported.

We propose a method for preventing hazardous accidents due to operator's action slip in their use of skill-assist, which has been already introduced as a power assist device in automobile assembly processes. First, we show that hidden Markov model (HMM) can be used to detect human erroneous operation from data sequences of an operator's hand motion trajectory, but that a problem arises in direct application of HMM to human error detection when trajectory is not in alignment with any of pretaught trajectories. However, HMM-based Dempster-Shafer theory proposed in the study allows the system to select their safety- or productivity- oriented robot control policy, solves the detection problem, and performs secure accident prevention, Second, a workability improvement process which comprises a state-policy and a teach data renewal sub-processes allows for optimal reconstruction of the policy determinant state space and HMMs. Finally, experimental results verify our overall proposal, and demonstrate the effectiveness of the workability improvement process.

The study concerns a human error recovery function for efficient human/robot collaborative parts conveyance tasks, which has not been discussed so far in construction of human/robot coexistence systems. We propose a human operational intention inference updater which allows a robot to judge whether the goal intended to reach by the operator is correct or not, from incomplete trajectory data sequence of the robot endtip maneuvered by the operator. Experimental results showed that a use of the proposed inference updater reduced the task execution time even when human error occurred in a task, which demonstrate the usefulness of the updater.

Recent advances in vision technology lead to the establishment of non-verbal communication channels from human behaviors toward understanding their intention. An adaptive vision-based attentive tracker (AVAT) is proposed for isolating such human intended actions from the ordinary walking behavior. The algorithm which drives the attentive tracker is divided into two sub-processes: one is for modeling the movement of human body parts as the environment using hidden Markov models, and the other is for learning the model of the tracker's action using a temporal difference algorithm. In the paper, we describe in detail the integration of the two sub-processes and finally show an experimental result of isolating the human sign action during his natural walking motion for demonstrating the feasibility of our proposal. Identification of the sign context determines the action of the tracker with the simulated rewards supplied.

It has been pointed out that the hard structure of an EVA glove deteriorates efficiency of tasks in the space environment. We also found a claim that an EVA glove did not allow an astronaut to acquire contact information at the fingertips. In the study, we proposed a SkilMate Hand for space EVA gloves which has both a tactile media and a power assist devices. We locate SkilMate in a wider framework of wearable intelligent machines which assist in affording such working surroundings that they can exhibit their skills in spite of their necessity for wearing special suits typically in hazardous environments. The paper focuses on the development of a finger system of a SkilMate Hand, and begins with determination of the design guidelines through analyses from an interview with an astronaut. To improve the task efficiency, we manufacture a power assist device which compensates the bending moment exerted at a human finger joint utilizing an ultrasonic motor. We show the structure and the control strategy of the motor drives. To overcome the second problem of tactile insensibleness, we produce a tactile media device which is composed of a slip sensor element on the outer side and a vibrotactile display element on the inner side of a SkilMate Hand. Transduction characteristics of both pressure sensitive conductive rubber and piezo-rubber are experimentally examined in the low temperature region. Finally, piezo-rubber is chosen to be used as a slip sensing transducer.

We develop a virtual sports training system for "playing catch". In this system, a force display device using "parallel wire mechanism" is adopted to obtain performance suitable for sports training. We describe the detail of the device used in this system. Furthermore, some basic experimental results demonstrate that it is capable of achieving the high speed performance enough to implement sports training.