scholarly journals Cognitively Intelligent Models for Human-Robot Interaction with MIRob

2021 ◽  
Vol 01 (01) ◽  
pp. 04-06
Author(s):  
Chapa Sirithunga ◽  
◽  
Buddhika Jayasekara ◽  

This research explores how a robot should gather knowledge upon a scenario between a robot and its user and then generate appropriate intelligent responses towards its user. Therefore, cognitive models were developed to act as a robot’s intelligence or the brain to make situation-specific decisions. Such insightful decisions will help the robot act in a social environment without disturbing its user or other humans around.

2017 ◽  
Author(s):  
Raz Leib ◽  
Andrea d’Avella ◽  
Ilana Nisky

AbstractThere are numerous ways to reach for an apple hanging from a tree. Yet, our motor system uses a specific muscle activity pattern to generate reaching movements that have similar characteristics. For many decades, we know that this pattern features activity bursts and silent periods. We suggest that these bursts are a strong evidence against the common view that the brain continuously controls the commands to the muscles. Instead, we suggest a model that changes these commands in a discrete way. We use unsupervised machine learning to identify transitions in the state of the muscles, and show that fitting a discrete model to the kinematics of movement using only one parameter predicts the transitions in the state of the muscles. Such discrete controller suggests that the brain reduces the complexity of the motor control problem as well as the wear-and-tear of the muscles by sending commands to the muscles at sparse times. Identifying this discrete controller can be applied in the control of prostheses and physical human-robot interaction systems such as exoskeletons and assistive devices.


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.


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