scholarly journals “I See What You Did There”

2021 ◽  
Vol 10 (3) ◽  
pp. 1-28
Author(s):  
Bob R. Schadenberg ◽  
Dennis Reidsma ◽  
Dirk K. J. Heylen ◽  
Vanessa Evers

Unpredictability in robot behaviour can cause difficulties in interacting with robots. However, for social interactions with robots, a degree of unpredictability in robot behaviour may be desirable for facilitating engagement and increasing the attribution of mental states to the robot. To generate a better conceptual understanding of predictability, we looked at two facets of predictability, namely, the ability to predict robot actions and the association of predictability as an attribute of the robot. We carried out a video human-robot interaction study where we manipulated whether participants could either see the cause of a robot’s responsive action or could not see this, because there was no cause, or because we obstructed the visual cues. Our results indicate that when the cause of the robot’s responsive actions was not visible, participants rated the robot as more unpredictable and less competent, compared to when it was visible. The relationship between seeing the cause of the responsive actions and the attribution of competence was partially mediated by the attribution of unpredictability to the robot. We argue that the effects of unpredictability may be mitigated when the robot identifies when a person may not be aware of what the robot wants to respond to and uses additional actions to make its response predictable.

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.


2018 ◽  
Vol 226 (2) ◽  
pp. 98-109 ◽  
Author(s):  
Antonella Marchetti ◽  
Federico Manzi ◽  
Shoji Itakura ◽  
Davide Massaro

Abstract. This review focuses on some relevant issues concerning the relationship between theory of mind (ToM) and humanoid robots. Humanoid robots are employed in different everyday-life contexts, so it seems relevant to question whether the relationships between human beings and humanoids can be characterized by a mode of interaction typical of the relationships between human beings, that is, the attribution of mental states. Because ToM development continuously undergoes changes from early childhood to late adulthood, we adopted a lifespan perspective. We analyzed contributions from the literature by organizing them around the partition between “mental states and actions” and “human-like features.” Finally, we considered how studying human–robot interaction, within a ToM context, can contribute to our understanding of the intersubjective nature of this interaction.


2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.


2011 ◽  
Vol 30 (5) ◽  
pp. 846-868 ◽  
Author(s):  
Estela Bicho ◽  
Wolfram Erlhagen ◽  
Luis Louro ◽  
Eliana Costa e Silva

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Jizheng Yan ◽  
Zhiliang Wang ◽  
Yan Yan

Emotional robots are always the focus of artificial intelligence (AI), and intelligent control of robot facial expression is a hot research topic. This paper focuses on the design of humanoid robot head, which is divided into three steps to achieve. The first step is to solve the uncanny valley about humanoid robot, to find and avoid the relationship between human being and robot; the second step is to solve the association between human face and robot head; compared with human being and robots, we analyze the similarities and differences and explore the same basis and mechanisms between robot and human analyzing the Facial Action Coding System (FACS), which guides us to achieve humanoid expressions. On the basis of the previous two steps, the third step is to construct a robot head; through a series of experiments we test the robot head, which could show some humanoid expressions; through human-robot interaction, we find people are surprised by the robot head expression and feel happy.


2019 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Agnieszka Wykowska

In our daily lives, we need to predict and understand others’ behaviour in order to navigate through our social environment. Predictions concerning other humans’ behaviour usually refer to their mental states, such as beliefs or intentions. Such a predictive strategy is called adoption of the intentional stance. In this paper, we review literature related to the concept of intentional stance from the perspectives of philosophy, psychology, human development, culture and human-robot interaction. We propose that adopting the intentional stance might be a central factor in facilitating social attunement with artificial agents. The paper first reviews the theoretical considerations regarding the intentional stance, and examines literature related to the development of intentional stance across the life span. Subsequently, it discusses cultural norms as grounded in the intentional stance and finally, it focuses on the issue of adopting the intentional stance towards artificial agents, such as humanoid robots. At the dawn of the artificial intelligence era, the question of how (and when) we predict and explain robots’ behaviour by referring to mental states is of high interest. The paper concludes with the discussion of the ethical consequences of robots towards which we adopt the intentional stance, and sketches future directions in research on this topic.


2020 ◽  
Vol 7 ◽  
Author(s):  
Shamil Mamedov ◽  
Stanislav Mikhel

Recently, with the increased number of robots entering numerous manufacturing fields, a considerable wealth of literature has appeared on the theme of physical human-robot interaction using data from proprioceptive sensors (motor or/and load side encoders). Most of the studies have then the accurate dynamic model of a robot for granted. In practice, however, model identification and observer design proceeds collision detection. To the best of our knowledge, no previous study has systematically investigated each aspect underlying physical human-robot interaction and the relationship between those aspects. In this paper, we bridge this gap by first reviewing the literature on model identification, disturbance estimation and collision detection, and discussing the relationship between the three, then by examining the practical sides of model-based collision detection on a case study conducted on UR10e. We show that the model identification step is critical for accurate collision detection, while the choice of the observer should be mostly based on computation time and the simplicity and flexibility of tuning. It is hoped that this study can serve as a roadmap to equip industrial robots with basic physical human-robot interaction capabilities.


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