We conducted R&D on wearable nursing robots as powered suits doubling as man-machine systems. In order to develop such a system, we studied physical static and dynamic considerations in designing assistance systems. We propose self-impedance matching (SIM) to evaluate system maneuverability based on energy flowing between the user and robot. The proposed SIM proved very effective in improving single-arm assistance maneuverability.

This paper describes electroencephalogram-based control of a mobile robot. The control purpose is to achieve direction control of a mobile robot only by electroencephalogram. We develop an algorithm for detecting direction thinking ('going left' or 'going right') and apply it to direction control of a mobile robot. The detecting algorithm is based on timefrequency domain analysis using continuous wavelet transformation. Our experimental results demonstrate the possibility of achieving direction control of a mobile robot only by electroencephalogram.

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The object of this paper is to give a g guide for designing the human-robot collaborative control system attaching importance to maneuverability of the operator. The operative ""feel"" is quantitatively evaluated using the norm of input-output signal obtained from the sensors during operation. As an example of the human-robot collaborative system, the subjective operative ""feel"" of the operator is qualitatively analyzed during the sine wave following task using 1-link operation arm. In addition, the control performance of the operator is examined from the viewpoint of H∞ control using the measurement data during the collaborative operation. As a result, it was suggested that the operator executes the given task while adequately reforming the sensitivity function and complementary sensitivity function of the closed loop system of the collaborative system. Use of this method enables design of the control system taking into consideration the operative ""feel"" of maneuverability.

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