339 research outputs found
Social robots in cognitive interventions. Advances, problems and perspectives
Social Assistive Robots are being used in therapeutic interventions for elderly people affected by cognitive impairments. The present paper reports our research lines aiming at investigating the role of a social robot in aiding therapists during cognitive stimulation sessions for elders with Mild Cognitive Impairment and Mild Dementia. We review our studies whose results show that social robots have been positively accepted by the seniors in different experiments. Participants were very attentive and involved in the sessions’ tasks and their experience was mainly positive. Our data suggest that this technology can be a valid tool to support psychotherapists in cognitive stimulation interventions emphasizing the need of multidisciplinary approaches combining assessment of behavior and robotics
PeppeRecycle: Improving Children’s Attitude Toward Recycling by Playing with a Social Robot
In this paper, we investigate the use of a social robot as an engaging interface of a serious game intended to make children more aware and well disposed towards waste recycle. The game has been designed as a competition between the robot Pepper and a child. During the game, the robot simultaneously challenges and teaches the child how to recycle waste materials. To endow the robot with the capability to play as a game opponent in a real-world context, it is equipped with an image recognition module based on a Convolutional Neural Network to detect and classify the waste material as a child would do, i.e. by simply looking at it. A formal experiment involving 51 primary school students is carried out to evaluate the effectiveness of the game in terms of different factors such as the interaction with the robot, the users’ cognitive and affective dimensions towards ecological sustainability, and the propensity to recycle. The obtained results are encouraging and draw promising scenarios for educational robotics in changing children’s attitudes toward recycling. Indeed Pepper turns out to be positively evaluated by children as a trustful and believable companion and this allows children to be concentrated on the “memorization” task during the game. Moreover, the use of real objects as waste items during the game turns out to be a successful approach not only for perceived learning effectiveness but also for the children’s engagement
Emotional design and human-robot interaction
Recent years have shown an increase in the importance of emotions applied to the Design field - Emotional Design. In this sense, the emotional design aims to elicit (e.g., pleasure) or prevent (e.g., displeasure) determined emotions, during human product interaction. That is, the emotional design regulates the emotional interaction between the individual and the product (e.g., robot). Robot design has been a growing area whereby robots are interacting directly with humans in which emotions are essential in the interaction. Therefore, this paper aims, through a non-systematic literature review, to explore the application of emotional design, particularly on Human-Robot Interaction. Robot design features (e.g., appearance, expressing emotions and spatial distance) that affect emotional design are introduced. The chapter ends with a discussion and a conclusion.info:eu-repo/semantics/acceptedVersio
Emotional social robot "Emotico"
This work presents high level design and preliminary results of the implementation of an psycho-emotional system based on DA and 5-HT subsystems implementing 4 basic emotions
Accessibility requirements for human-robot interaction for socially assistive robots
Mención Internacional en el título de doctorPrograma de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: María Ángeles Malfaz Vázquez.- Secretario: Diego Martín de Andrés.- Vocal: Mike Wal
Affective Computing for Human-Robot Interaction Research: Four Critical Lessons for the Hitchhiker
Social Robotics and Human-Robot Interaction (HRI) research relies on
different Affective Computing (AC) solutions for sensing, perceiving and
understanding human affective behaviour during interactions. This may include
utilising off-the-shelf affect perception models that are pre-trained on
popular affect recognition benchmarks and directly applied to situated
interactions. However, the conditions in situated human-robot interactions
differ significantly from the training data and settings of these models. Thus,
there is a need to deepen our understanding of how AC solutions can be best
leveraged, customised and applied for situated HRI. This paper, while
critiquing the existing practices, presents four critical lessons to be noted
by the hitchhiker when applying AC for HRI research. These lessons conclude
that: (i) The six basic emotions categories are irrelevant in situated
interactions, (ii) Affect recognition accuracy (%) improvements are
unimportant, (iii) Affect recognition does not generalise across contexts, and
(iv) Affect recognition alone is insufficient for adaptation and
personalisation. By describing the background and the context for each lesson,
and demonstrating how these lessons have been learnt, this paper aims to enable
the hitchhiker to successfully and insightfully leverage AC solutions for
advancing HRI research.Comment: 11 pages, 3 figures, 1 tabl
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