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A Taxonomy in Robot-Assisted Training: Current Trends, Needs and Challenges

Konstantinos Tsiakas, Maria Kyrarini, Vangelis Karkaletsis, Fillia Makedon, Oliver Korn

发表年份
2018
引用次数
21
访问权限
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摘要

In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human–Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical training task. Robot-Assisted Training systems have been successfully deployed to enhance the effects of a training session in various contexts, i.e., rehabilitation systems, educational environments, vocational settings, etc. The proposed taxonomy suggests a set of categories and parameters that can be used to characterize such systems, considering the current research trends and needs for the design, development and evaluation of Robot-Assisted Training systems. To this end, we review recent works and applications in Robot-Assisted Training systems, as well as related taxonomies in Human–Robot Interaction. The goal is to identify and discuss open challenges, highlighting the different aspects of a Robot-Assisted Training system, considering both robot perception and behavior control.

关键词

RobotHuman–computer interactionComputer scienceTask (project management)Session (web analytics)Taxonomy (biology)Set (abstract data type)Human–robot interactionArtificial intelligenceEngineering

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