A Cognitive Framework for Learning by Imitation

Abstract

Abstract – In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of a cognitive framework for learning by imitation in which a rich conceptual representation of the observed actions is built. The proposed architecture has been tested on the robotic system composed of a PUMA 200 industrial manipulator and an anthropomorphic robotic hand. The system demonstrated the ability to classify and imitate a rich set of movement primitives acquired through the vision system for manipulative purposes. 1.