Article published In: Interaction Studies
Vol. 7:3 (2006) ► pp.369–403
An approach for a social robot to understand human relationships
Friendship estimation through interaction with robots
Published online: 15 November 2006
https://doi.org/10.1075/is.7.3.12kan
https://doi.org/10.1075/is.7.3.12kan
This paper reports our research efforts on social robots that recognize interpersonal relationships. These investigations are carried out by observing group behaviors while the robot interacts with people. Our humanoid robot interacts with children by speaking and making various gestures. It identifies individual children by using a wireless tag system, which helps to promote interaction such as the robot calling a child by name. Accordingly, the robot is capable of interacting with many children, causing spontaneous group behavior from the children around it. Here, group behavior is associated with social relationships among the children themselves. For example, a child may be accompanied by his or her friends and then play together with them. We propose the hypothesis that our interactive robot prompts a child’s friends to accompany him or her; thus, we can estimate their friendship by simply observing their accompanying behaviors.
We conducted a field experiment for two weeks in a Japanese elementary school to verify this hypothesis. In the experiment, two “Robovie” robots were placed where children could freely interact with them during recesses. As a result, we found that they mostly prompted friend-accompanying behavior. Moreover, we could estimate some of their friendly relationships, in particular among the children who often appeared around the robot. For example, we could estimate 5% of all friendships with 80% accuracy, and 15% of them with nearly 50% accuracy. Thus, this result basically supports our hypothesis on friendship estimation from an interactive humanoid robot. We believe that this ability to estimate human relationships is essential for robots to behave socially.
Cited by (15)
Cited by 15 other publications
Fraile, Marc, Natalia Calvo-Barajas, Anastasia Sophia Apeiron, Giovanna Varni, Joakim Lindblad, Nataša Sladoje & Ginevra Castellano
Fraile, Marc, Giovanna Varni, Joakim Lindblad, Nataša Sladoje & Ginevra Castellano
Pandey, Amit Kumar
Abbasi, Nida Itrat, Micol Spitale, Peter B. Jones & Hatice Gunes
2022. Measuring mental wellbeing of children via human-robot interaction. Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems 23:2 ► pp. 157 ff.
Abe, Kasumi, Takayuki Nagai, Chie Hieida, Takashi Omori & Masahiro Shiomi
Komatsubara, Tsuyoshi, Masahiro Shiomi, Thomas Kaczmarek, Takayuki Kanda & Hiroshi Ishiguro
Shiomi, Masahiro, Tsuyoshi Komatsubara, Thomas Kaczmarek, Takayuki Kanda & Hiroshi Ishiguro
Sim, Doreen Ying Ying & Chu Kiong Loo
Ng, Wing W. Y., Tian-Ming Zheng, Patrick P. K. Chan & Daniel S. Yeung
Tung, Fang-Wu
Mavridis, Nikolaos, Wajahat Kazmi & Panos Toulis
Robins, Ben, Farshid Amirabdollahian, Ze Ji & Kerstin Dautenhahn
Hagita, Norihiro, Masahiro Shiomi, Hiroshi Ishiguro & Takayuki Kanda
This list is based on CrossRef data as of 30 march 2026. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.
