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  • 2018

  • Ozaki, Yasunori; Ishihara, Tatsuya; Matsumura, Narimune; Nunobiki, Tadashi; Yamada, Tomohiro (2018) : Decision-Making Prediction for Human-Robot Engagement between Pedestrian and Robot Receptionist In: Cabibihan, John-Joh: IEEE RO-MAN 2018: The 27th IEEE International Symposium on Robot and Human Interactive Communication: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing: 8/27/2018 - 8/31/2018. Ro-Man; Institute of Electrical and Electronics Engineers; IEEE Robotics and Automation Society; IEEE Ro-Man; IEEE International Symposium on Robot and Human Interactive Communication: Piscataway, NJ: IEEE, S. 208-215

    Abstract: Social robots have been providing a number of customer services lately. For example, they can take the place of people as receptionists. When people interact they predict each others decision-making from the others actions and take suitable actions for the sake of the other. However, taking such actions is difficult for modern social robots. Therefore, our initial aim is to solve the problem of how to predict decision-making in human-robot engagement. Choosing a reception system as a case study to approach this goal, we created a new model to predict who will use the system. The model contains a state transition function based on observation studies. We evaluated the model though a controlled experiment and a simulation experiment, using field data on prediction performance and mental effect. The experiment results lead us to believe that the model can predict the decisions of others sufficiently well. We also found that a pedestrian who will not talk with a robot receptionist suffers a negative emotion when the pedestrian is greeted by a robot, but a method we propose prevents this. We suggest that the word suitable is related to negative emotion, a part of usability. By using our model in the future we will attempt to find a method that will enable a robot to learn suitable actions by itself.

  • 2014

  • Henkel, Z.; Bethel, C. L.; Murphy, R. R.; Srinivasan, V. (2014): Evaluation of Proxemic Scaling Functions for Social Robotics. In: IEEE Transactions on Human-Machine Systems 44 (3), S. 374-385. DOI: 10.1109/THMS.2014.2304075

    DOI: https://doi.org/10.1109/THMS.2014.2304075 

    Abstract: This paper introduces and empirically evaluates two scaling functions to alter a robot’s physical movements based on proximity to a human. Previous research has focused on individual aspects of proxemics, like the appropriate distance to maintain from a human, but has not explored autonomous methods to adapt robot behavior as proximity changes. This paper proposes that robots in a social role should modify their behavior using a continuous function mapped to proximity. The method developed calculates a gain value from proximity readings, which is used to shape the execution of active behaviors on the robot. In order to identify the effects of different mappings from proximity to gain value, two different scaling functions were implemented on an affective search and rescue robot. The findings from a 72 participant study, in a high-fidelity mock disaster site, are examined with attention given to a new measure to determine proxemic awareness. The results indicated that for attributes of intelligence, likability, proxemic awareness, and submissiveness, a logarithmic-based scaling function is preferred over a linear-based scaling function, and over no scaling function. In areas of participant comfort and participant stress, the results indicated both logarithmic and linear scaling functions were preferred to no scaling.

  • Złotowski, J.; Strasser, E.; Bartneck, C. (2014) : Dimensions of Anthropomorphism : From Humanness to Humanlikeness In: Sagerer, Gerhard; Imai, Michita; Belpaeme, Tony; Thomaz, Andrea (Hg.): HRI'14: Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction : March 3-6, 2014, Bielefeld, Germany. Unter Mitarbeit von Gerhard Sagerer und Michita Imai: the 2014 ACM/IEEE international conference: Bielefeld, Germany: 3/3/2014 - 3/6/2014. Hri; Association for Computing Machinery; Institute of Electrical and Electronics Engineers; IEEE Robotics and Automation Society; ACM/IEEE International Conference on Human-Robot Interaction: Piscataway, NJ: IEEE, S. 66-73

    Abstract: In HRI anthropomorphism has been considered to be a unidimensional construct. However, social psychological studies of the potentially reverse process to anthropomorphisation - known as dehumanization - indicate that there are two distinct senses of humanness with different consequences for people who are dehumanized by deprivation of some of the aspects of these dimensions. These attributes are crucial for perception of others as humans. Therefore, we hypothesized that the same attributes could be used to anthropomorphize a robot in HRI and only a two-dimensional measures would be suitable to distinguish between different forms of making a robot more humanlike. In a study where participants played a quiz based on the TV show “Jeopardy!” we manipulated a NAO robot's intelligence and emotionality. The results suggest that only emotionality, not intelligence, makes robots be perceived as more humanlike. Furthermore, we found some evidence that anthropomorphism is a multidimensional phenomenon.

  • 2013

  • Joosse, M.; Lohse, M.; Pérez, J. G.; Evers, V. (2013) : What you do is who you are: The role of task context in perceived social robot personality: 2013 IEEE International Conference on Robotics and Automation: Karlsruhe, Germany: IEEE, S. 2134-2139

    DOI: https://doi.org/10.1109/ICRA.2013.6630863 

    Abstract: People tend to unconsciously attribute personality traits to all kinds of technology including robots. But what personality do they want robots to have? Previous research has found support for two contradicting theories: similarity attraction and complementary attraction. The similarity attraction theory implies that people prefer a robot with a similar personality to their own (e.g., an extroverted person prefers an extroverted robot). According to the complementary attraction theory, people prefer a robot’s personality opposite to their own (e.g., extroverted people prefer an introverted robot). In contrast to both theories, we argue that what is considered an appropriate personality for a robot depends on the task context. In a 2×2 between-groups experiment (N=45), we found trends that indicated similarity attraction for extrovert participants when the robot was a tour guide and complementary attraction for introverted participants when the robot was a cleaner. These trends show that preferences for robot personalities may indeed depend on the context of the robot’s role and the stereotype perceptions people hold for certain jobs. Robot behaviors likely need to be adapted not in complimentary or similarity to the users’ personality but to the users’ expectations about what kind of personality and behaviors are consistent with such a task or role.

  • 2011

  • Häring, M.; Bee, N.; André, E. (2011) : Creation and Evaluation of emotion expression with body movement, sound and eye color for humanoid robots: 2011 RO-MAN: 2011 RO-MAN: Georgia, USA: IEEE, S. 204-209

    DOI: https://doi.org/10.1109/ROMAN.2011.6005263 

    Abstract: The ability to display emotions is a key feature in human communication and also for robots that are expected to interact with humans in social environments. For expressions based on Body Movement and other signals than facial expressions, like Sound, no common grounds have been established so far. Based on psychological research on human expression of emotions and perception of emotional stimuli we created eight different expressional designs for the emotions Anger, Sadness, Fear and Joy, consisting of Body Movements, Sounds and Eye Colors. In a large pre-test we evaluated the recognition ratios for the different expressional designs. In our main experiment we separated the expressional designs into their single cues (Body Movement, Sound, Eye Color) and evaluated their expressivity. The detailed view at the perception of our expressional cues, allowed us to evaluate the appropriateness of the stimuli, check our implementations for flaws and build a basis for systematical revision. Our analysis revealed that almost all Body Movements were appropriate for their target emotion and that some of our Sounds need a revision. Eye Colors could be identified as an unreliable component for emotional expression.

  • Mumm, J.; Mutlu, B. (2011) : Human-robot proxemics: Physical and psychological distancing in human-robot interaction: 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI): 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI): New York, NY, US: Association for Computing Machinery, S. 331-338

    DOI: https://doi.org/10.1145/1957656.1957786 

    Abstract: To seamlessly integrate into the human physical and social environment, robots must display appropriate proxemic behavior-that is, follow societal norms in establishing their physical and psychological distancing with people. Social-scientific theories suggest competing models of human proxemic behavior, but all conclude that individuals’ proxemic behavior is shaped by the proxemic behavior of others and the individual’s psychological closeness to them. The present study explores whether these models can also explain how people physically and psychologically distance themselves from robots and suggest guidelines for future design of proxemic behaviors for robots. In a controlled laboratory experiment, participants interacted with Wakamaru to perform two tasks that examined physical and psychological distancing of the participants. We manipulated the likeability (likeable/dislikeable) and gaze behavior (mutual gaze/averted gaze) of the robot. Our results on physical distancing showed that participants who disliked the robot compensated for the increase in the robot’s gaze by maintaining a greater physical distance from the robot, while participants who liked the robot did not differ in their distancing from the robot across gaze conditions. The results on psychological distancing suggest that those who disliked the robot also disclosed less to the robot. Our results offer guidelines for the design of appropriate proxemic behaviors for robots so as to facilitate effective human-robot interaction.

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