Towards enhancing the understanding of human motor learning

Abstract

The research on human-robot interaction (HRI) has been an emerging topic of interest for both basic research and customer application. The studies specially focus on behavioral and cognitive aspects of the interaction and the social contexts surrounding it. HRI issues have long been a part of robotics research because the goal of fully autonomous capability has not been met yet. One of the most challenging problems is giving the robots an understanding of how to interact with human beings at the same logical level so that they may function not as passive tools, but rather as active agents that can drive the human interaction, instead of merely reproducing a sequence of movements. Hence, these robots must have higher level cognitive functions that include knowing how to reason, when to perceive and what to look for, how to integrate perception and action under changing conditions, etc. These functions will enable robots to perform more complex tasks which require tight human interaction; consequently, the robots can perform high level interactions such as teaching motor skills to unskilled people. In this paper, the development of active training systems for medical training purposes designed to provide quantitative information as well as to provide feedback to medical students are detailed.