A study of effective social cues within ubiquitous robotics

Sandygulova, Anara; Swords, David; Abdel-Naby, Sameh; O’Hare, Gregory M. P.; Dragone, Mauro

doi:10.1109/hri.2013.6483581

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…In the Social Robotics domain, the outsourcing of services to third-party services in the cloud mostly concerns the aspects already mentioned in Section I: (i) dialogue [18,19], (ii) activity planning [20,21,22,23], (iii) collective learning [24,25,26,27], and (iv) perception [28,29,30,31].…”

Section: A Cloud-based Social Roboticsmentioning

confidence: 99%

“…One approach to achieve this is to equip a cloud application with a range of encyclopedic knowledge under the form of an Ontology, and execution logs of different robots performing the same tasks in different environments. In a similar spirit, [25] and [26] describe a collective learning environment for ubiquitous robots. Sensors embedded in these robots can provide vast amounts of information that can be beneficial in further processing and collective learning.…”

Section: A Cloud-based Social Roboticsmentioning

confidence: 99%

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Sustainable Verbal and Non-verbal Human-Robot Interaction Through Cloud Services

Grassi¹,

Recchiuto²,

Sgorbissa³

2022

Preprint

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This article presents the design and the implementation of CAIR: a cloud system for knowledge-based autonomous interaction devised for Social Robots and other conversational agents. The system is particularly convenient for low-cost robots and devices. Developers are provided with a sustainable solution to manage verbal and non-verbal interaction through a network connection, with about 3,000 topics of conversation ready for "chit-chatting" and a library of pre-cooked plans that only needs to be grounded into the robot's physical capabilities. The system is structured as a set of REST API endpoints so that it can be easily expanded by adding new APIs to improve the capabilities of the clients connected to the cloud. Another key feature of the system is that it has been designed to make the development of its clients straightforward: in this way, multiple devices can be easily endowed with the capability of autonomously interacting with the user, understanding when to perform specific actions, and exploiting all the information provided by cloud services. The article outlines and discusses the results of the experiments performed to assess the system's performance in terms of response time, paving the way for its use both for research and market solutions. Links to repositories with clients for ROS and popular robots such as Pepper and NAO are given.

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