Abstract
Recently, with the development of the robot industry, various types of robots have been developed, and robots are being used in various fields as well as industrial fields. Many studies show the possibility of extending the development direction of such companion robots to education and show many research cases. Especially for children, social interaction training during infancy and childhood has a great impact as an adult. Among them, social initiation, which means trying social interaction first, requires sufficient training and interaction experience. So, it is necessary to understand the meaning of social initiation in which the robot attempts social interaction in a situation where the user is concentrating on the task. Learning from robots is effective for infants and young children, and the intimacy formed by social initiation of robots can maximize the learning effect. For those reason, in a 1:1 interaction between the user and the robot, we understand how social initiation of the robot can attract the user’s attention when the user is concentrating on the task, and what form of social initiation forms the social intimacy between the user and the robot. In particular, this study conducted an experiment focusing on the change in user’s interest and liking according to the language type of the robot among the social initiation types, and the results were derived. This study examined the characteristics of robot social initiation targeting adults first and further work is planned to extend the result to children.
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Acknowledgements
This work was supported by the Technology Innovation Program (20015161, AI Butler Service for Facilitating Socialization of Family Members in Their Daily Life) funded By the Ministry of Trade, industry & Energy (MOTIE, Korea).
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Choi, J., Kim, MG., Han, D., Lee, W., Lee, W. (2023). Analysis of Changes in User’s Attention on Characteristics of Social Initiation of a Robot in 1:1 Interaction Between a User and a Robot. In: Jo, J., et al. Robot Intelligence Technology and Applications 7. RiTA 2022. Lecture Notes in Networks and Systems, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-031-26889-2_37
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DOI: https://doi.org/10.1007/978-3-031-26889-2_37
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