A Unified Model For Developmental Robotics

Abstract

We present the architecture and distributed algorithms of an implemented system called NeuSter, that unifies learning, perception and action for autonomous robot control. NeuSter comprises several sub-systems that provide online learning for networks of million neurons on machine clusters. It extracts information from sensors, builds its own representations of the environment in order to learn non-predefined goals.