We have been developing robotic exoskeletons to assist motion of physi-cally weak persons such as elderly, disabled, and injured persons. The robotic exoskeleton is controlled basically based on the electromyogram (EMG) signals, since the EMG signals of human muscles are important signals to understand how the user intends to move. Even though the EMG signals contain very important in-formation, however, it is not very easy to predict the user’s upper-limb motion (elbow and shoulder mo-tion) based on the EMG signals in real-time because of the difficulty in using the EMG signals as the controller input signals. In this paper, we propose a robotic exoskeleton for human upper-limb motion as-sist, a hierarchical neuro-fuzzy controller for the robotic exoskeleton, and its adaptation method.

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