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In this study, we propose a control method for movement assistive robots using measured signals from human users. Some of the wearable assistive robots have mechanisms that can be adjusted to human kinematics (e.g., adjustable link length). However, since the human body has a complicated joint structure, it is generally difficult to design an assistive robot which mechanically well fits human users. We focus on the development of a control algorithm to generate corresponding movements of wearable assistive robots to that of human users even when the kinematic structures of the assistive robot and the human user are different. We first extract the latent kinematic relationship between a human user and the assistive robot. The extracted relationship is then used to control the assistive robot by converting human behavior into the corresponding joint angle trajectories of the robot. The proposed approach is evaluated by a simulated robot model and our newly developed exoskeleton robot, XoR.

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