Abstract-In this paper, we propose a role adaptation method for human-robot shared control. Game theory is employed for fundamental analysis of this two-agent system. An adaptation law is developed such that the robot is able to adjust its own role according to the human's intention to lead or follow, which is inferred through the measured interaction force. In the absence of human interaction forces, the adaptive scheme allows the robot to take the lead and complete the task by itself. On the other hand, when the human persistently exerts strong forces that signal an unambiguous intent to lead, the robot yields and becomes the follower. Additionally, the full spectrum of mixed roles between these extreme scenarios is afforded by continuous online update of the control that is shared between both agents. Theoretical analysis shows that the resulting shared control is optimal with respect to a two-agent coordination game. Experimental results illustrate better overall performance, in terms of both error and effort, compared to fixed-role interactions.
This article presents a study with five children with autism who were involved in a game. As relatively little work has been done on using robots in a classroom setting for children with autism, this paper investigates the potential use of robots as an educational companion for children with autism in a classroom setting. The target users were pre-schoolers diagnosed with high-functioning autism. The aim of the study was to find out how turn-taking games with a robot among the children could encourage social interaction skills in children with autism. Behavioral criteria such as eye gaze and touch were evaluated using video data. Based on our observation, autistic children with low social communication scores have a lower ratio of eye contact compare to autistic children with high social communication. The analysis of behavioral observations also revealed that the autistic children with higher scores of social communication skills directed significantly more eye gaze and touch towards the robot. This finding supports the idea that robot was suitable for encouraging interaction. But the results reveal a need for long term studies in order to establish the full benefits of using robots in the classroom for children with autism.
Abstract-In this paper, a role adaptation method is developed for human-robot collaboration based on game theory. This role adaptation is engaged whenever the interaction force changes, causing the proportion of control sharing between human and robot to vary. In one boundary condition, the robot takes full control of the system when there is no human intervention. In the other boundary condition, it becomes a follower when the human exhibits strong intention to lead the task. Experimental results show that the proposed method yields better overall performance than fixed-role interactions.
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