People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

This paper deals with a tangible interface system that introduces robot as remote avatar. It is focused on a new method which makes a robot imitate human arm motions captured from a remote space. Our method is functionally divided into two parts: capturing human motion and adapting it to robot. In the capturing part, we especially propose a modified potential function of metaballs for the real-time performance and high accuracy. In the adapting part, we suggest a geometric scaling method for solving the structural difference between a human and a robot. With our method, we have implemented a tangible interface and showed its speed and accuracy test.