Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces

Saida Mussakhojayeva; Nazerke Kalidolda; Anara Sandygulova

doi:10.1007/978-3-319-70022-9_74

Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces

Saida Mussakhojayeva, Nazerke Kalidolda, Anara Sandygulova

Department of Robotics and Mechatronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

In order to inform the important considerations when designing robotic applications for public spaces, the focus of this research is to investigate what socio-psychological effects should influence robot’s decision-making within public environments. Social environments are often complex and ambiguous: many queries to the robot are collaborative (e.g. a family), but in case of conflicting queries, social robots need to participate in value decisions and negotiating multi-party interactions. With the aim to investigate who should robots adapt to (children or adults) in multi-party situations within human-robot interactions in public spaces, this paper presents a real-world study conducted in a shopping mall. The results include a number of interesting findings based on people’s relationship with a child and their parental status.

Original language	English
Title of host publication	Social Robotics - 9th International Conference, ICSR 2017, Proceedings
Editors	Kenji Suzuki, Hongsheng He, Abderrahmane Kheddar, Eiichi Yoshida, Friederike Eyssel, Shuzhi Sam Ge, John-John Cabibihan
Publisher	Springer Verlag
Pages	749-758
Number of pages	10
ISBN (Print)	9783319700212
DOIs	https://doi.org/10.1007/978-3-319-70022-9_74
Publication status	Published - 2017
Event	9th International Conference on Social Robotics, ICSR 2017 - Tsukuba, Japan Duration: Nov 22 2017 → Nov 24 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10652 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on Social Robotics, ICSR 2017
Country	Japan
City	Tsukuba
Period	11/22/17 → 11/24/17

Keywords

Human-robot interaction
Multi-party interaction
Public spaces
Social robotics

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-70022-9_74

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Mussakhojayeva, S., Kalidolda, N., & Sandygulova, A. (2017). Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces. In K. Suzuki, H. He, A. Kheddar, E. Yoshida, F. Eyssel, S. S. Ge, & J-J. Cabibihan (Eds.), Social Robotics - 9th International Conference, ICSR 2017, Proceedings (pp. 749-758). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10652 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-70022-9_74

Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces. / Mussakhojayeva, Saida; Kalidolda, Nazerke; Sandygulova, Anara.

Social Robotics - 9th International Conference, ICSR 2017, Proceedings. ed. / Kenji Suzuki; Hongsheng He; Abderrahmane Kheddar; Eiichi Yoshida; Friederike Eyssel; Shuzhi Sam Ge; John-John Cabibihan. Springer Verlag, 2017. p. 749-758 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10652 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mussakhojayeva, S, Kalidolda, N & Sandygulova, A 2017, Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces. in K Suzuki, H He, A Kheddar, E Yoshida, F Eyssel, SS Ge & J-J Cabibihan (eds), Social Robotics - 9th International Conference, ICSR 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10652 LNAI, Springer Verlag, pp. 749-758, 9th International Conference on Social Robotics, ICSR 2017, Tsukuba, Japan, 11/22/17. https://doi.org/10.1007/978-3-319-70022-9_74

Mussakhojayeva S, Kalidolda N, Sandygulova A. Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces. In Suzuki K, He H, Kheddar A, Yoshida E, Eyssel F, Ge SS, Cabibihan J-J, editors, Social Robotics - 9th International Conference, ICSR 2017, Proceedings. Springer Verlag. 2017. p. 749-758. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-70022-9_74

Mussakhojayeva, Saida ; Kalidolda, Nazerke ; Sandygulova, Anara. / Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces. Social Robotics - 9th International Conference, ICSR 2017, Proceedings. editor / Kenji Suzuki ; Hongsheng He ; Abderrahmane Kheddar ; Eiichi Yoshida ; Friederike Eyssel ; Shuzhi Sam Ge ; John-John Cabibihan. Springer Verlag, 2017. pp. 749-758 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In order to inform the important considerations when designing robotic applications for public spaces, the focus of this research is to investigate what socio-psychological effects should influence robot{\textquoteright}s decision-making within public environments. Social environments are often complex and ambiguous: many queries to the robot are collaborative (e.g. a family), but in case of conflicting queries, social robots need to participate in value decisions and negotiating multi-party interactions. With the aim to investigate who should robots adapt to (children or adults) in multi-party situations within human-robot interactions in public spaces, this paper presents a real-world study conducted in a shopping mall. The results include a number of interesting findings based on people{\textquoteright}s relationship with a child and their parental status.",

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Adaptive Strategies for Multi-party Interactions with Robots in Public Spaces

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