In order to eliminate the drawbacks of conventional force feedback gloves, a new type of master hand has been developed. By utilizing three ¿four-bar mechanism joint¿ in series and wire coupling mechanism, the master finger transmission ratio is kept exact 1:1.4:1 in the whole movement range and it can make active motions in both extension and flexion direction. Additionally, to assure faster data transmission and near zero delay in master-slave operation, a digital signal processing/field programmable gate array (DSP/FPGA-FPGA) structure with 200 ¿s cycle time is designed. The operating modes of the master hand can be contact or non-contact, which depends on the motion states of slave hand, free motion or constrained motion. The position control employed in non-contact mode ensures unconstrained motion and the force control adopted in contact mode guarantees natural contact sensation. To evaluate the performances of the master hand, an master-slave control experiment based on force-position control method between the master hand and DLR/HIT hand is conducted. The results demonstrate this new type master hand can augment telepresence.

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In this paper, hardware implementation of control and interface between two robots for teleoperation tasks are designed and implemented on two field programmable gate array(FPGA) chips. The first FPGA chip is designed for collecting data from the master robot which is the motion capturing device that captures motions of a human operator who wears it. The second FPGA chip is used for controlling motions of the slave robot which is the humanoid robot arms as a counter part of the master robot. Captured motions from the master robot are transferred to the slave robot to follow the movement after the master robot. All hardware design such as PED controllers, communication modules between two robots, encoder counters, and PWM generators are implemented on an FPGA chip. Experimental studies of motion following tasks are conducted to demonstrate the FPGA controller design.

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In this paper it is shown how variation of the kinematic structure of an arm exoskeleton and variation of its fixation pressure on the human limb influences subjectively perceived task performance, such as comfort and the individual indices of the NASA TLX rating scale. It is shown by experimental results that the attachment pressure has a dominant effect on perceived comfort, mental load, physical demand and effort experienced by subjects and is optimal within a range of 10 30 mmHg. Furthermore, it is shown that the inclusion of passive compensatory joints inside an exoelectrons structure can reduce mental demand during a tracking task. When the outcome of this paper is interpreted in combination with a set of objective performance results that were presented earlier , the subjective performance metrics underline the fact that passive compensatory joints paired with an attachment pressure of 20 mmHg increase ergonomics and provide optimal conditions for task performance and comfort.

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We address an exoskeletal type haptic device which helps the human actively feel the sense of touch in palmar and dorsal directions. The device consisting of two finger-like parts taken by thumb and index finger, is designed in modular type to expand easily for five fingers. The proposed device is semi-directly driven by ultrasonic motors which have high power-to-weight ratio, and it provides haptic feedback to each joint of fingers. Methods for measuring the angular displacements and torques of the fingers are proposed and basic experiments are performed to verify the effectiveness of the system

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In this paper, a model based interactive torque estimation method for exoskeletons is proposed. For this purpose, the dynamic model based disturbance observer (DOB) is adopted to estimate the interactive torque instead of using force/torque sensors. Also, a parameter identification method is applied to enhance the precision of estimated torque against various uncertainties in the dynamic model. In order to classify interactive torque from the estimated disturbance signal of DOB, the information on generated actuator torque is required. By the actuator impedance model, the generated actuator torque can be estimated precisely. The proposed methods were implemented in SUBAR (Sogang University’s Biomedical Assist Robot) and verified by experiments.

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