Behavior Coordination of A Partner Robot based on Imitation

This paper proposes behavior coordination based on imitation of a partner robot interacting with a human. First of all, we discuss the ro le of imitation, and explain the method for imitative behavior generation. The robot searches for a human by using a CCD camera. A human hand motion pattern is extracted from a series of images taken from the CCD camera. Next, the position sequence of the extracted human hand is used as inputs to a spiking neural network to recognize it as a gesture. The trajectory for a behavior is generated and updated by a steady-state genetic algorithm based on human moti ons. Furthermore, a self-organizing map is used for clustering human hand motion patterns as gestures. Fi nally, we show experimental results of imitative behavior generation and behavior coordination through interaction with a human.