Social Human-Robot Interaction: A New Cognitive and Affective Interaction-Oriented Architecture

Adam, Carole; Johal, Wafa; Pellier, Damien; Fiorino, Humbert; Pesty, Sylvie

doi:10.1007/978-3-319-47437-3_25

Cited by 20 publications

(14 citation statements)

References 21 publications

(18 reference statements)

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“…In particular, for robots engaged in social HRI, the implementation of some of these cognitive abilities—or of them as a whole architecture—has been demonstrated in the context of autonomous social interaction (Adam et al, 2016 ; McColl et al, 2016 ), in studies aimed at the employment of joint action (Lemaignan et al, 2017 ) as well as in studies where the robot is assisting the humans in achieving their goals (Beer et al, 2014 ).…”

Section: Cognitive Architecturesmentioning

confidence: 99%

A Socially Adaptable Framework for Human-Robot Interaction

et al. 2020

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In our everyday lives we regularly engage in complex, personalized, and adaptive interactions with our peers. To recreate the same kind of rich, human-like interactions, a social robot should be aware of our needs and affective states and continuously adapt its behavior to them. Our proposed solution is to have the robot learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers. To make the robot autonomous in its decision making, this process could be guided by an internal motivation system. We wish to investigate how an adaptive robotic framework of this kind would function and personalize to different users. We also wish to explore whether the adaptability and personalization would bring any additional richness to the human-robot interaction (HRI), or whether it would instead bring uncertainty and unpredictability that would not be accepted by the robot's human peers. To this end, we designed a socially adaptive framework for the humanoid robot iCub. As a result, the robot perceives and reuses the affective and interactive signals from the person as input for the adaptation based on internal social motivation. We strive to investigate the value of the generated adaptation in our framework in the context of HRI. In particular, we compare how users will experience interaction with an adaptive versus a non-adaptive social robot. To address these questions, we propose a comparative interaction study with iCub whereby users act as the robot's caretaker, and iCub's social adaptation is guided by an internal comfort level that varies with the stimuli that iCub receives from its caretaker. We investigate and compare how iCub's internal dynamics would be perceived by people, both in a condition when iCub does not personalize its behavior to the person, and in a condition where it is instead adaptive. Finally, we establish the potential benefits that an adaptive framework could bring to the context of repeated interactions with a humanoid robot.

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Section: Cognitive Architecturesmentioning

confidence: 99%

A Socially Adaptable Framework for Human-Robot Interaction

et al. 2020

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“…Similar to human-human interaction during cognitive training by human therapists, robots need to be able to interact with users naturally in robotic rehabilitation. This includes having a good understanding of user's emotions (e.g., happiness, shame, engagement), intentions and personality (Pettinati and Arkin, 2015 ; Rahbar et al, 2015 ; Vaufreydaz et al, 2016 ; Rudovic et al, 2018 ), being able to provide an emotional response when being shared with personal information (de Graaf et al, 2015 ; Chumkamon et al, 2016 ), talking day-by-day more to the user on various topics like hobbies, and dealing with novel events (Dragone et al, 2015 ; Kostavelis et al, 2015 ; Adam et al, 2016 ; Ozcana et al, 2016 ). These natural user-robot interactions require powerful perception, reasoning, acting and learning modules in robots, or in other words, cognitive and social-emotional capabilities.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review of Robotic Rehabilitation for Cognitive Training

et al. 2021

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A large and increasing number of people around the world experience cognitive disability. Rehabilitation robotics has provided promising training and assistance approaches to mitigate cognitive deficits. In this article, we carried out a systematic review on recent developments in robot-assisted cognitive training. We included 99 articles in this work and described their applications, enabling technologies, experiments, and products. We also conducted a meta analysis on the articles that evaluated robot-assisted cognitive training protocol with primary end users (i.e., people with cognitive disability). We identified major limitations in current robotics rehabilitation for cognitive training, including the small sample size, non-standard measurement of training and uncontrollable factors. There are still multifaceted challenges in this field, including ethical issues, user-centered (or stakeholder-centered) design, the reliability, trust, and cost-effectiveness, personalization of the robot-assisted cognitive training system. Future research shall also take into consideration human-robot collaboration and social cognition to facilitate a natural human-robot interaction.

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“…Conversely to other studies (Adam et al 2016;Charisi et al 2018;Robert 2018), no influence regarding how they felt about rapport building with the robot and their performance in the activity was found in this experiment, as they rated the second meeting less enjoyable than the first one (4.91 against 4.69) in item 1, although there was no significant difference. This can be associated with the novelty and their expectation of the unknown at the first interaction.…”

Section: Students Perception With Regard To the Robotcontrasting

confidence: 99%

Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)

Tozadore¹

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To the hero of all adventures, my father Marcos. And to love itself, my mother Herminia, my eternal gratitude for always encouraging my inner child and all the sweet things I carry in my heart. I would also like to take the opportunity to thank all my grandparents, uncles, aunts, cousins and the "Galera" family in helping my parents in this mission. To my legendary best friends: Juliana, Michele and Rafael-whom I have the fortune of having as siblings-no matter how much time passes, nothing is ever legendary without your presence. I will be there for you because I want in that way. My sincere thanks to my supervisor, professor Roseli Romero, for her extraordinary work with me, for all the hours of joy and sadness together and for having matured so much and in so many aspects of my life. I will miss you very much and I know wherever I will be in my future, I will always be brilliant because you believed in me and always dreamed with me. To my older brother Daniel Ferras, born from different parents but bonded by music, thank you for supporting me all the time with your advice and your melody. A very special thanks to my lab-mates, of flesh or metal, from the "Laboratório de aprendizado de Robôs", who lovingly suffered this journey with me, especially my very good friend and admired researcher Dr. Adam Moreira and my favorite workmate, Teddy the robot. Thank you to the under-grad students that I had the honor of mentoring; João Valentini,

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Social Human-Robot Interaction: A New Cognitive and Affective Interaction-Oriented Architecture

Cited by 20 publications

References 21 publications

A Socially Adaptable Framework for Human-Robot Interaction

A Socially Adaptable Framework for Human-Robot Interaction

A Systematic Review of Robotic Rehabilitation for Cognitive Training

Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)

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