To assist physically disabled, injured, and/or elderly persons, we have been developing a 3DOF exoskeleton robot for assisting upper-limb motion, since upper-limb motion is involved in a lot of activities of everyday life. The exoskeleton robot is mainly is controlled by the skin surface electromyogram (EMG) signals, since EMG signals of muscles directly reflect how the user intends to move. This paper introduces the mechanism of the exoskeleton robot and also proposes a control method of the exoskeletonrobot considering the generated end-effector force vectors.

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The Berkeley Lower Extremity Exoskeleton is the first functional ener-getically autonomous load carrying human exoskeleton and was demonstrated at U.C. Berkeley, walking at the average speed of 0.9 m/s (2 mph) while carrying a 34 kg (75 lb) payload. The original published control-ler, called the BLEEX Sensitivity Amplification Controller, was based on positive feedback and was designed to increase the closed loop system sensitivity to its wearer’s forces and torques without any direct measurement from the wearer. This controller was successful at allowing natural and unobstructed load support for the pilot. This article presents an improved control scheme we call “hybrid” BLEEX con-trol that adds robustness to changing BLEEX backpack payload. The walking gait cycle is divided into stance control and swing control phases. Position control is used for the BLEEX stance leg (including the torso and backpack) and a sensitivity amplification controller is used for the swing leg. The controller is also designed to smoothly transition between these two schemes as the pilot walks. With hybrid control, the controller does not require a good model of the BLEEX torso and payload, which is difficult to obtain and subject to change as payload is added and removed. As a tradeoff, the position control used in this method requires the human to wear seven inclinometers to measure human limb and torso angles. These addi-tional sensors require careful design to securely fasten them to the human and increase the time to don and doff BLEEX.

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The integration of human and robot into a single system offers remar-kable opportunities for a new generation of assistive technology. Despite the recent prominence of upper limb exoskeletons in assistive applications, the human arm kinematics and dynamics are usually described in single or multiple arm movements that are not associated with any concrete activity of daily living(ADL). Moreover, the design of an exoskeleton, which is physically linked to the human body, must have a workspace that matches as close as possible with the workspace of the human body, while at the same time avoid singular configurations of the exoskeleton within the human workspace. The aims of the research reported in this manuscript are to study the kinematics and the dynamics of the human arm during daily activities in a free and unconstrained environment, to study the manipulability (isotropy) of a 7-degree-of-freedom (DOF)-powered exoskeleton arm given the kinematics and the dynamics of the human arm in ADLs. Kinematic data of the upper limb were acquired with a motion capture system while performing 24 daily activities from six subjects. Utilising a 7-DOF model of the human arm, the equations of motion were used to calculate joint torques from measured kinematics. In addition, the exoskeleton isotropy was calculated and mapped with respect to the spacial distribution of the human arm configurations during the 24 daily activities. The results indicate that the kinematic joint distributions representing all 24 actions appear normally distributed except for elbow flexion–extension with the emergence of three modal centres. Velocity and acceleration components of joint torque distributions were normally distributed about 0 Nm, whereas gravitational component distributions varied with joint. Additionally, velocity effects were found to contribute only 1/100th of the total joint torque, whereas acceleration components contribute 1/10th of the total torque at the shoulder and elbow, and nearly half of the total torque at the wrist. These re-sults suggest that the majority of human arm joint torques are devoted to supporting the human arm posi-tion in space while compensating gravitational loads whereas a minor portion of the joint torques is dedicated to arm motion itself. A unique axial orientation at the base of the exoskeleton allowed the singular configuration of the shoulder joint to be moved towards the boundary of the human arm workspace while supporting 95% of the arm’s workspace. At the same time, this orientation allowed the best exoskele-ton manipulability at the most commonly used human arm configuration during ADLs. One of the potential implications of these results might be the need to compensate gravitational load during robotic-assistive rehabilitation treatment. Moreover, results of a manipulability analysis of the exoskeleton system indicate that the singular configuration of the exoskeleton system may be moved out of the human arm physiological workspace while maximising the overlap between the human arm and the exoskeleton workspaces. The collected database along with kinematic and dynamic analyses may provide a fundamental basis towards the development of assistive technologies for the human arm.

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A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash, and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of space and weight limitations, workspace requirements, and the kinematic constraints placed on the device by the human arm. These constraints impose conflicting design requirements on the engineer attempting to design an arm exoskeleton. In this paper, the authors present a detailed review of the requirements and constraints that are involved in the design of a high-quality haptic arm exoskeleton. In this context, the design of a five-degree-of-freedom haptic armexoskeleton for training and rehabilitation in virtual environments is presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. As a training tool, the device provides a means to implement flexible, repeatable, and safe training methodologies.

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An operating status of a motor in a drive unit is analyzed to extend the life of the motor. A wearable motion assistive device 1 includes a shoulder joint mechanism 5 and an elbow joint mechanism 6 for aiding a movement of the shoulder joint and the elbow joint, and a control unit 100 having a control circuit for controlling drive units 11 for the shoulder and elbow joint mechanisms 5 and 6. The control unit 100 controls the drive units 11 based on a physical quantity and a biosignal detected by an angle sensor, a torque sensor, and a biosignal detecting sensor. A controller in the drive unit 11 includes a motor monitoring unit for monitoring an operational status of the motor, and a motor control unit for limiting a drive signal supplied to the motor based on a monitoring result provided by the motor monitoring unit, in order to prevent an overload state of the motor.

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