  This study proposes an imitation learning method based on force and position
information. Force information is required for precise object manipulation but
is difficult to obtain because the acting and reaction forces cannnot be
separated. To separate the forces, we proposed to introduce bilateral control,
in which the acting and reaction forces are divided using two robots. In the
proposed method, two models of neural networks learn a task; to draw a line
along a ruler. We verify the possibility that force information is essential to
imitate the human skill of object manipulation.
