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- Volume 17, Issue, 2016
Interaction Studies - Volume 17, Issue 3, 2016
Volume 17, Issue 3, 2016
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Do relative positions and proxemics affect the engagement in a Human-Robot collaborative scenario?
Author(s): Fotios Papadopoulos, Dennis Küster, Lee J. Corrigan, Arvid Kappas and Ginevra Castellanopp.: 321–347 (27)More LessThis paper investigates the effects of relative position and proxemics in the engagement process involved in Human-Robot collaboration. We evaluate the differences between two experimental placement conditions (frontal vs. lateral) for an autonomous robot in a collaborative task with a user across two different types of robot behaviours (helpful vs. neutral). The study evaluated placement and behaviour types around a touch table with 80 participants by measuring gaze, smiling behaviour, distance from the task, and finally electrodermal activity. Results suggest an overall user preference and higher engagement rates with the helpful robot in the frontal position. We discuss how behaviours and position of the robot relative to a user may affect user engagement and collaboration, in particular when the robot aims to provide help via socio-emotional bonding.
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Why do children abuse robots?
Author(s): Tatsuya Nomura, Takayuki Kanda, Hiroyoshi Kidokoro, Yoshitaka Suehiro and Sachie Yamadapp.: 347–369 (23)More LessWe found that children sometimes abused a social robot placed in a shopping mall hallway. They verbally abused the robot, repeatedly obstructed its path, and sometimes even kicked and punched the robot. To investigate the reasons for the abuse, we conducted a field study in which we interviewed visiting children who exhibited serious abusive behaviors, including physical contact. We analyzed interview contents to determine whether the children perceived the robot as human-like, why they abused it, and whether they thought that the robot would suffer from their abusive behavior. We obtained valid interviews from 23 children (age range, 5–9 years old) over 13 days of observations. We found that 1) the majority of the children engaged in abuse because they were curious about the robot’s reactions or enjoyed abusing it and considered it human-like, and 2) about half of them believed the robot was capable of perceiving their abusive behaviors.
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Does successful small-scale coordination help or hinder coordination at larger scales?
Author(s): Seth Frey and Robert L. Goldstonepp.: 371–389 (19)More LessAn individual can interact with the same set of people over many different scales simultaneously. Four people might interact as a group of four and, at the same time, in pairs and triads. What is the relationship between different parallel interaction scales, and how might those scales themselves interact?
We devised a four-player experimental game, the Modular Stag Hunt, in which participants chose not just whether to coordinate, but with whom, and at what scale. Our results reveal coordination behavior with such a strong preference for dyads that undermining pairwise coordination actually improves group-scale outcomes. We present these findings as experimental evidence for competition, as opposed to complementarity, between different possible scales of multi-player coordination. This result undermines a basic premise of approaches, like those of network science, that fail to model the interacting effects of dyadic, triadic, and group-scale structures on group outcomes.
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The Effects of Exposure to Different Social Robots on Attitudes toward Preferences
Author(s): Evgenios Vlachos, Elizabeth Jochum and Louis-Philippe Demerspp.: 390–404 (15)More LessWe present results of a quasi-experimental study investigating how user preference might change after direct interaction with two different types of robot regarding morphology and affordances: a machine-like that interacts through touch, and a human-like that interacts verbally. The study was performed in an art exhibition setting, where visitors had the opportunity to interact with the robots voluntarily, and were asked to fill out questionnaires before and after the experience. Post interactions, visitors preferred to touch the machine-like “hard” robot despite initial stated preference for soft materials, preferred mutual contact despite initial preference of subject to initiate touch, and preferred communication with a robot that could touch rather than initial preference for a robot that could “see”. Overall, users showed a significant constant preference for the machine-like robot, reportedly feeling a stronger connection with it than with the human-like one as it met their expectations, and they found its movements more appealing. Social conditioning can render people reluctant to touch a robot with very human-like appearance, and set the expectations for interaction too high to meet. Our results, lastly, indicate that interaction with more than one type of social robot can affect the interaction experience for each of the robots.
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New Frontiers in Human-Robot Interaction
Author(s): Maha Salem, Astrid Weiss and Paul Baxterpp.: 405–407 (3)More Less
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Robots Showing Emotions
Author(s): Julian M. Angel-Fernandez and Andrea Bonarinipp.: 408–437 (30)More LessRobots should be able to represent emotional states to interact with people as social agents. There are cases where robots cannot have bio-inspired bodies, for instance because the task to be performed requires a special shape, as in the case of home cleaners, package carriers, and many others. In these cases, emotional states have to be represented by exploiting movements of the body. In this paper, we present a set of case studies aimed at identifying specific values to convey emotion trough changes in linear and angular velocities, which might be applied on different non-anthropomorphic bodies. This work originates from some of the most considered emotion expression theories and from emotion coding for people. We show that people can recognize some emotional expressions better than others, and we propose some directions to express emotions exploiting only bio-neutral movement.
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Robot-Mediated interviews with Children
Author(s): Luke Jai Wood, Hagen Lehmann, Kerstin Dautenhahn, Ben Robins, Austen Rainer and Dag Sverre Syrdalpp.: 438–460 (23)More LessTo date research investigating the potential of Robot-Mediated Interviews (RMI) has focused on establishing how children respond to robots in an interview scenario. In order to test if an RMI approach would work in a real world setting, it is important to establish what the experts (e.g. specialist child interviewers) would require from such a system. To determine the needs of such expert users we conducted three user panels with groups of potential real world users to gather their views of our current system and find out what they would require for the system to be useful to them. The user groups consisted of specialist police officers, intermediaries, educational specialists and healthcare specialists. To our knowledge this is the first article investigating user needs for Robot-Mediated Interviews. Due to the novelty of this area, the work presented in this paper is exploratory in nature. The results provide valuable insights into what real world users would need from a Robot-Mediated Interviewing system. Our findings will contribute to future research and technology development in the domain of RMI in particular, and child-robot interaction in general.
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Long-term evaluation of a social robot in real homes
Author(s): Maartje M. A. de Graaf, Somaya Ben Allouch and Jan A. G. M. van Dijkpp.: 462–491 (30)More LessThis study aims to contribute to emerging human-robot interaction research by adding longitudinal findings to a limited number of long-term social robotics home studies. We placed 70 robots in users’ homes for a period of up to six months, and used questionnaires and interviews to collect data at six points during this period. Results indicate that users’ evaluations of the robot dropped initially, but later rose after the robot had been used for a longer period of time. This is congruent with the so-called mere-exposure effect, which shows an increasing positive evaluation of a novel stimulus once people become familiar with it. Before adoption, users focus on control beliefs showing that previous experiences with robots or other technologies allows to create a mental image of what having and using a robot in the home would entail. After adoption, users focus on utilitarian and hedonic attitudes showing that especially usefulness, social presence, enjoyment and attractiveness are important factors for long-term acceptance.
Volumes & issues
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Volume 24 (2023)
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Socially Acceptable Robot Behavior
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Volume 23 (2022)
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Volume 22 (2021)
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Volume 21 (2020)
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Volume 20 (2019)
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Volume 19 (2018)
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Volume 18 (2017)
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Volume 17 (2016)
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Volume 16 (2015)
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Volume 15 (2014)
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Volume 14 (2013)
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Volume 13 (2012)
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Volume 12 (2011)
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Volume 11 (2010)
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Volume 10 (2009)
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Volume 9 (2008)
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Volume 8 (2007)
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Volume 7 (2006)
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Volume 6 (2005)
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Volume 5 (2004)