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2017
Mussakhojayeva, S.; Sandygulova, A. (2017) : Cross-cultural differences for adaptive strategies of robots in public spaces: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Lisbon, Portugal: IEEE Robotics & Automation Society, S. 573-578

DOI: https://doi.org/10.1109/ROMAN.2017.8172360

Abstract: Robots deployed in public spaces must necessarily deal with situations that demand them to engage humans in a socially and culturally appropriate manner. However, social environments are often complex and ambiguous: many queries to the robot are collaborative (e.g. a family), and in case of conflicting queries, social robots need to participate in value decisions and negotiating multi-party interactions. Given the strong influence of the people’s demographic information and social schema among people, such as relationships and hierarchies, the focus of this research is to examine whether and how people exhibit socio-psychological effects with a shared robot deployed at international events or spaces (e.g. airports). With the aim to investigate who robots should adapt to (children or adults) in multi-party situations within human-robot interactions in public spaces and whether this adaptation can be influenced by culture, this paper presents a cross-cultural study conducted online. The results include a number of interesting findings based on people’s relationship with a child and their parental status. In addition, a number of cross-cultural differences were identified in respondents’ attitude towards robot’s multi-party adaptation in various public settings.

Keywords: Airports, Angemessen(heit) (von Technik), control engineering computing, cross-cultural differences, cultural aspects, Cultural differences, Face recognition, Foot, human-robot interaction, human-robot interactions, ieee xplore, multiparty adaptation, PSYCHOLOGY, public spaces, Robots, social robots, socio-psychological effects, speech, Videos
Shiarlis, K.; Messias, J.; Whiteson, S. (2017) : Acquiring social interaction behaviours for telepresence robots via deep learning from demonstration: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Vancouver, British Columbia, Canada: IEEE, S. 37-42

DOI: https://doi.org/10.1109/IROS.2017.8202135

Abstract: As robots begin to inhabit public and social spaces, it is increasingly important to ensure that they behave in a socially appropriate way. However, manually coding social behaviours is prohibitively difficult since social norms are hard to quantify. Therefore, learning from demonstration (LfD), wherein control policies are inferred from demonstrations of correct behaviour, is a powerful tool for helping robots acquire social intelligence. In this paper, we propose a deep learning approach to learning social behaviours from demonstration. We apply this method to two challenging social tasks for a semi-autonomous telepresence robot. Our results show that our approach outperforms gradient boosting regression and performs well against a hard-coded controller. Furthermore, ablation experiments confirm that each element of our method is essential to its success.

Keywords: ablation experiments, challenging social tasks, Cloning, control engineering computing, correct behaviour, deep learning approach, deep learning from demonstration, gradient boosting regression, gradient methods, hard-coded controller, human-robot interaction, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), LfD, machine learning, public spaces, Regression Analysis, Robot sensing systems, semiautonomous telepresence robot, social behaviour, Social intelligence, social interaction behaviours, Social Norms, social spaces, telepresence robots
2016
Mussakhojayeva, S.; Zhanbyrtayev, M.; Agzhanov, Y.; Sandygulova, A. (2016) : Who should robots adapt to within a multi-party interaction in a public space?: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Christchurch, New Zealand: IEEE Press, S. 483-484

DOI: https://doi.org/10.1109/HRI.2016.7451817

Abstract: Robots in public environments are challenged with socially appropriate interactions with previously unseen users: they need to offer appropriate services and shape their interaction style according to the particular individual’s needs and preferences, for example the elderly and children. In addition, interactions in public spaces are not limited to merely two parties, but often involve multi-party situations with changing numbers of participants. The research question of this work is to investigate what rules should a socially competent robot follow in order to adapt to such complex social situations in real-world scenarios.

Keywords: Analysis of Variance, Angemessen(heit) (von Technik), complex social situations, Hospitals, Humanoid Robots, human-robot interaction, ieee xplore, Information exchange, intelligent robots, Legged locomotion, multiparty interaction, Multi-Party Interaction, public environments, public spaces, real-world scenarios, Robot sensing systems, service robot, Social robotic, socially appropriate interactions, socially competent robot, speech, user needs, user preferences

2017

2016

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