  Imitation learning has been actively studied in recent years. In particular,
skill acquisition by a robot with a fixed body, whose root link position and
posture and camera angle of view do not change, has been realized in many
cases. On the other hand, imitation of the behavior of robots with floating
links, such as humanoid robots, is still a difficult task. In this study, we
develop an imitation learning system using a biped robot with a floating link.
There are two main problems in developing such a system. The first is a
teleoperation device for humanoids, and the second is a control system that can
withstand heavy workloads and long-term data collection. For the first point,
we use the whole body control device TABLIS. It can control not only the arms
but also the legs and can perform bilateral control with the robot. By
connecting this TABLIS with the high-power humanoid robot JAXON, we construct a
control system for imitation learning. For the second point, we will build a
system that can collect long-term data based on posture optimization, and can
simultaneously move the robot's limbs. We combine high-cycle posture generation
with posture optimization methods, including whole-body joint torque
minimization and contact force optimization. We designed an integrated system
with the above two features to achieve various tasks through imitation
learning. Finally, we demonstrate the effectiveness of this system by
experiments of manipulating flexible fabrics such that not only the hands but
also the head and waist move simultaneously, manipulating objects using legs
characteristic of humanoids, and lifting heavy objects that require large
forces.
