Analyze the Cooperative Skills of Leadership and Followership using Machine Learning

Abstract

This paper focused on cooperative skills in order to investigate physical human interaction key factors using a cooperative model. Human interaction is made up of both verbal and nonverbal communication. Especially, force communication has drawn a lot of attention as a means of nonverbal communication. Several studies focus on force communication, however, these studies have not considered human skills. In particular, cooperative skill is important for Human-Human interaction (HHI) or Human-Robot interaction (HRI). This paper proposes the neural networks that learn the CFO. CFO is estimated by comparison with learning the input command during the solo task using neural networks and the input command during the cooperative task. Also, this paper analyzes physical human interaction using the data which is compressed information by neural networks. In the experiment, the proposed neural networks can predict CFO precisely. In addition, the results show that followership on cooperative skills is induced by other players.