Author:
Dragone Mauro,Saunders Joe,Dautenhahn Kerstin
Abstract
AbstractEnabling robots to seamlessly operate as part of smart spaces is an important and extended challenge for robotics R&D and a key enabler for a range of advanced robotic applications, such as AmbientAssisted Living (AAL) and home automation. The integration of these technologies is currently being pursued from two largely distinct view-points: On the one hand, people-centred initiatives focus on improving the user’s acceptance by tackling human-robot interaction (HRI) issues, often adopting a social robotic approach, and by giving to the designer and - in a limited degree – to the final user(s), control on personalization and product customisation features. On the other hand, technologically-driven initiatives are building impersonal but intelligent systems that are able to pro-actively and autonomously adapt their operations to fit changing requirements and evolving users’ needs, but which largely ignore and do not leverage human-robot interaction and may thus lead to poor user experience and user acceptance. In order to inform the development of a new generation of smart robotic spaces, this paper analyses and compares different research strands with a view to proposing possible integrated solutions with both advanced HRI and online adaptation capabilities.
Subject
Behavioral Neuroscience,Artificial Intelligence,Cognitive Neuroscience,Developmental Neuroscience,Human-Computer Interaction
Reference1 articles.
1. A general purpose distributed learning model for robotic ecologies in Proceedings of the th International IFAC Symposium on Robot Control vol pp;Bacciu;SYROCO,2012
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