Visuo-motor learning for behavior generation of humanoids

This paper proposes a method of behavior generation for humanoids in which a robot learns sensorimotor maps in each motion module as the forward and inverse relationships between optic flows in the robot´s view and motion parameters. Humanoids use these maps to determine appropriate motion parameters that generate a desired flow given by a planner. Each module consists of a planner and sensorimotor maps of primitives and can accomplish a simple task. Using a predefined module transition rule, humanoids can accomplish a complex task. Passing a ball (face-to-face pass) between two humanoids which have different camera lens and body parameters is realized as an example task.