A robotic model of the development of gaze following

Abstract

For humanoid robots, the skill of gaze following is a foundational component in social interaction and imitation learning.We present a robotic system capable of learning the gaze following behavior in a real-world environment. First, the system learns to detect salient objects and to distinguish a caregiverpsilas head poses in a semi-autonomous manner. Then we present multiple scenes containing different combinations of objects and head poses to the robot head. The system learns to associate the detected head pose with correct spatial location of where potentially ldquorewardingrdquo objects would be using a biologically plausible reinforcement learning mechanism.