Abstract
Humanoid robots should be able to handle independently human bodies. In previous studies, robots manipulated human bodies using brute force, but this does not accurately reflect a human's action. Yoshinori Kouno, who has studied several skills related to physical exertion, including martial arts and nursing-care motions possesses, as the subject, we studied these motions and analyzed the techniques that were superior to other body dynamics. In this study, we focused on the pushing action of human, and aimed to understand the body's dynamics. The zero moment point (ZMP) trajectories of the actor varied around the center of gravity (COG), and the actor used the falling momentum to push the recipient's body. Kouno reported that the position of the fingers enabled him to control his arm movements. Hence we analyzed the electromyogram signals of the whole body. Analysis of the recipient's resistance based on the ZMP and COG, suggests that the recipient can predict the attack by the actor of the action and braces him/herself for the impact. Thus, the actor needs to confound the recipient's prediction to realize human pushing motions with less effort. The falling momentum strategy and change in the arm's force play an important role to in confusing the prediction. We confirm the effectiveness of these body dynamics using numerical simulation. Finally, we conclude that the “knack” of the pushing motion is due to a special pose of fingers.
