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Social robots are robots interacting with humans not only in collaborative settings, but also in personal settings like domestic services and healthcare. Some social robots simulate feelings (companions) while others just help lifting (assistants). However, they often incite both fascination and fear: what abilities should social robots have and what should remain exclusive to humans? We provide a historical background on the development of robots and related machines (1), discuss examples of social robots (2) and present an expert study on their desired future abilities and applications (3) conducted within the Forum of the European Active and Assisted Living Programme (AAL). The findings indicate that most technologies required for the social robots' emotion sensing are considered ready. For care robots, the experts approve health-related tasks like drawing blood while they prefer humans to do nursing tasks like washing. On a larger societal scale, the acceptance of social robots increases highly significantly with familiarity, making health robots and even military drones more acceptable than sex robots or child companion robots for childless couples. Accordingly, the acceptance of social robots seems to decrease with the level of face-to-face emotions involved.
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.