IEEE TNNLS, SPECIAL ISSUE ON LEARNING IN NONSTATIONARY AND EVOLVING ENVIRONMENTS 1 Developmental Perception of the Self and Action

Abstract—This paper describes a developmental framework for action-driven perception in anthropomorphic robots. The key idea of the framework is that action generation develops the agent’s perception of its own body and actions. Action-driven development is critical for identifying changing body parts and understanding the effects of actions in unknown or non-stationary environments. We embedded minimal knowledge into the robot’s cognitive system in the form of motor synergies and actions to allow motor exploration. The robot voluntarily generates actions and develops the ability to perceive its own body and the effect that it generates on the environment. The robot, moreover, can compose this kind of learned primitives to perform complex actions and characterize them in terms of their sensory effects. After learning, the robot can recognize manipulative human behaviors with cross-modal anticipation for recovery of unavailable sensory modality, and reproduce the recognized actions afterwards. We evaluated the proposed framework in experiments with a real robot. In the experiments, we achieved autonomous body identification, learning of fixation, reaching and grasping actions, and developmental recognition of human actions as well as their reproduction