Implementation of a Framework for Imitation Learning on a Humanoid Robot Using a Cognitive Architecture

Abstract

Robots are designed to assist human beings to complete tasks. As described in many research journals and scientific fictions, researchers and the general public expect that one day robots can complete certain tasks independently and autonomously in our world. A typical implementation of Artificial Intelligence (AI) in robotics research is expected to incorporate Knowledge Representation, Automated Reasoning, Machine Learning, and Computer Vision [Russell and Norvig, 2010]. From the beginning of this century, the importance of cognitive sciences is highlighted by the researchers in both robotics and artificial intelligences[Russell and Norvig, 2010]. Real Cognitive Science is based on the testing and experiments on animals and humans to obtain the understanding and knowledge of the cognition, and AI research is based on designing and testing algorithms on a computer based artificial system. In the development, research in both Cognitive Sciences and AI benefit each other. Cognitive Science provides theoretical foundation and solutions to the problems in AI, and AI enhances the research in Cognitive Science and provides possible research directions for Cognitive Science. Recently, an emerging field, named Cognitive Robotics, is developed for robots to generate human-like behaviors and intelligences, which integrates perception, action, learning, decision-making, and communication[Kawamura and Browne, 2009]. Cognitive Robotics largely incorporates the concepts in the research of cognitive sciences and tries to simulate the architecture of the information processing of human cognition. Currently, some long term requirements are proposed for Cognitive Robotics, which put concentration on the embodiment of cognitive concepts [Anderson, 2003; Sloman et al., 2006]. Increasing achievements in Cognitive Robotics began to grab the attention of the robotics research community. However, currently, it is still difficult to design truly cognition, especially human-like cognition, on a robotic platform due to the limitations in mechanism, computation, architecture, etc. [Brooks, 1991]. Therefore, on one side, researchers try to place robots in a human-existing dynamic environment to complete tasks[Brooks, 1991]; on the other side, researchers still do not obtain a general architecture to generate complex behaviors in such area for robots[Sloman, 2001]. In recent research, researchers try to place robots in robotic aid area, where robots can assist humans to complete tasks[Tan et al., 2005].