Real-time arm motion imitation for human–robot tangible interface

Yukyung Choi, SyungKwon Ra, Soowhan Kim, Sung-Kee Park

Abstract: In this paper, we deal with a remote meeting system with a tangible interface, in which a robot is used as a tangible avatar instead of a remote meeting partner. For realizing such a system, it is a critical issue of how the robot imitates human motions with natural and exact. So, we suggested a new method that human arm motion is captured with a stereo vision system and transferred to the robotic avatar in real-time. For capturing 3D arm motions based on the markerless method, we proposed a new metaball-based method that was designed in order to have some robust and efficient properties: a modified iso-surface equation of metaball for overcoming local minima and a downsizing method of 3D point cloud for improving time complexity. With our meeting system, we have implemented our new algorithm and run at approximately 12–16 Hz. Also, its accuracy in motion capturing could be acceptable for robot motion generation.