scholarly journals MemoRob: Studying Robots Distractor Effects

2020 ◽  
Vol 81 (1-4) ◽  
pp. 55-61
Author(s):  
Céline Jost ◽  
Brigitte Le Pévédic ◽  
Marine Grandgeorge ◽  
Marie Le Menn ◽  
Farah Arab ◽  
...  

MemoRob is a model about how to optimize the use of robots for learning. It is based on a list of each possible robotic source of distraction associated with its relevant effects according to its nature and to the target learning mode. While collecting the sources of distraction that the robotics literature provides, the instantiation method of pairing each source and each learning mode with the nature of the distraction as well as its distracting effects allows to consider how to remedy these effects of robotic distraction effects although still having the robotic input as a learning medium. In this article, we provide the motivations that led to the need for the MemoRob model, the list of sources and effects generated by the Human-Robot interaction that may interfere with learning situations, the learning modes described according to their processes and mechanisms and, finally, a set of predictions on whether a given robotic learning situations might promote attention or distraction.

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 222
Author(s):  
Remko Proesmans ◽  
Andreas Verleysen ◽  
Robbe Vleugels ◽  
Paula Veske ◽  
Victor-Louis De Gusseme ◽  
...  

Smart textiles have found numerous applications ranging from health monitoring to smart homes. Their main allure is their flexibility, which allows for seamless integration of sensing in everyday objects like clothing. The application domain also includes robotics; smart textiles have been used to improve human-robot interaction, to solve the problem of state estimation of soft robots, and for state estimation to enable learning of robotic manipulation of textiles. The latter application provides an alternative to computationally expensive vision-based pipelines and we believe it is the key to accelerate robotic learning of textile manipulation. Current smart textiles, however, maintain wired connections to external units, which impedes robotic manipulation, and lack modularity to facilitate state estimation of large cloths. In this work, we propose an open-source, fully wireless, highly flexible, light, and modular version of a piezoresistive smart textile. Its output stability was experimentally quantified and determined to be sufficient for classification tasks. Its functionality as a state sensor for larger cloths was also verified in a classification task where two of the smart textiles were sewn onto a piece of clothing of which three states are defined. The modular smart textile system was able to recognize these states with average per-class F1-scores ranging from 85.7 to 94.6% with a basic linear classifier.


2014 ◽  
Author(s):  
Mitchell S. Dunfee ◽  
Tracy Sanders ◽  
Peter A. Hancock

Author(s):  
Rosemarie Yagoda ◽  
Michael D. Coovert

2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna

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.


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.


Author(s):  
José Novoa ◽  
Jorge Wuth ◽  
Juan Pablo Escudero ◽  
Josué Fredes ◽  
Rodrigo Mahu ◽  
...  

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