Making New "New AI" Friends : Designing a Social Robot for Diabetic Children from an Embodied AI Perspective

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Robin is a cognitively and motivationally autonomous affective robot toddler with "robot diabetes" that we have developed to support perceived self-efficacy and emotional wellbeing in children with diabetes by providing them with positive mastery experiences of diabetes management in a playful but realistic and natural interaction context. Underlying the design of Robin is an "Embodied" (formerly also known as "New") Artificial Intelligence approach to robotics. In this paper we discuss the rationale behind the design of Robin to meet the needs of our intended end users (both children and medical staff), and how "New AI" provides a suitable approach to developing a friendly companion that fulfills the therapeutic and affective requirements of our end users beyond other approaches commonly used in assistive robotics and child-robot interaction. Finally, we discuss how our approach permitted our robot to interact with and provide suitable experiences of diabetes management to children with very different social interaction styles.Peer reviewedFinal Published versio

Hedonic Quality or Reward? A Study of Basic Pleasure in Homeostasis and Decision Making of a Motivated Autonomous Robot

© The Author (s) 2016. Published by SAGE. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).We present a robot architecture and experiments to investigate some of the roles that pleasure plays in the decision making (action selection) process of an autonomous robot that must survive in its environment. We have conducted three sets of experiments to assess the effect of different types of pleasure---related versus unrelated to the satisfaction of physiological needs---under different environmental circumstances. Our results indicate that pleasure, including pleasure unrelated to need satisfaction, has value for homeostatic management in terms of improved viability and increased flexibility in adaptive behavior.Peer reviewedFinal Published versio

Developing sensorimotor associations through attachment bonds.

Attachment bonds and positive affect help cognitive development and social interactions in infants and animals. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object. We also discuss how our research on attachment bonds could further developmental robotics in the near future. 1

Using the interaction rhythm as a natural reinforcement signal for social robots: a matter of belief

The original publication is available at www.springerlink.com Copyright Springer VerlagIn this paper, we present the results of a pilot study of a human robot interaction experiment where the rhythm of the interaction is used as a reinforcement signal to learn sensorimotor associations. The algorithm uses breaks and variations in the rhythm at which the human is producing actions. The concept is based on the hypothesis that a constant rhythm is an intrinsic property of a positive interaction whereas a break reflects a negative event. Subjects from various backgrounds interacted with a NAO robot where they had to teach the robot to mirror their actions by learning the correct sensorimotor associations. The results show that in order for the rhythm to be a useful reinforcement signal, the subjects have to be convinced that the robot is an agent with which they can act naturally, using their voice and facial expressions as cues to help it understand the correct behaviour to learn. When the subjects do behave naturally, the rhythm and its variations truly reflects how well the interaction is going and helps the robot learn efficiently. These results mean that non-expert users can interact naturally and fruitfully with an autonomous robot if the interaction is believed to be natural, without any technical knowledge of the cognitive capacities of the robot.Peer reviewe

Assessing human reactions to different robot attachment profiles

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ROMAN.2009.5326216Emotional regulation is believed to be crucial for a balanced emotional and cognitive development in infants. Furthermore, during the first year of a child's life, the mother is playing a central role in shaping the development, through the attachment bond she shares with her child. Based on previous work on our model of arousal modulation for an autonomous robot, we present an experiment where human adults were interacting visually and via tactile contact with a SONY Aibo robot exploring a children playmat. The robots had two different attachment profiles: one recquiring less attention then the other. The subjects answered one questionnaire per robot, describing how they would rate their experience with each robot. The analysis of the subjects' responses allow us to conclude that this setting was sufficient to elicit positive and active caretaking-like behaviours from the subjects, according to the profile of the robot they interacted with

Interpretation of emotional body language displayed by robots

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.In order for robots to be socially accepted and generate empathy they must display emotions. For robots such as Nao, body language is the best medium available, as they do not have the ability to display facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should greatly improve its acceptance. This research investigates the creation of an "Affect Space" [1] for the generation of emotional body language that could be displayed by robots. An Affect Space is generated by "blending" (i.e. interpolating between) different emotional expressions to create new ones. An Affect Space for body language based on the Circumplex Model of emotions [2] has been created. The experiment reported in this paper investigated the perception of specific key poses from the Affect Space. The results suggest that this Affect Space for body expressions can be used to improve the expressiveness of humanoid robots. In addition, early results of a pilot study are described. It revealed that the context helps human subjects improve their recognition rate during a human-robot imitation game, and in turn this recognition leads to better outcome of the interactions

Eliciting Caregiving Behavior in Dyadic Human-Robot Attachment-Like Interactions

We present here the design and applications of an arousal-based model controlling the behavior of a Sony AIBO robot during the exploration of a novel environment: a children’s play mat. When the robot experiences too many new perceptions, the increase of arousal triggers calls for attention towards its human caregiver. The caregiver can choose to either calm the robot down by providing it with comfort, or to leave the robot coping with the situation on its own. When the arousal of the robot has decreased, the robot moves on to further explore the play mat. We gathered results from two experiments using this arousal-driven control architecture. In the first setting, we show that such a robotic architecture allows the human caregiver to influence greatly the learning outcomes of the exploration episode, with some similarities to a primary care- giver during early childhood. In a second experiment, we tested how human adults behaved in a similar setup with two different robots: one “needy”, often demanding attention, and one more independent, requesting far less care or assistance. Our results show that human adults recognise each profile of the robot for what they have been designed, and behave accordingly to what would be expected, caring more for the needy robot than for the other. Additionally, the subjects exhibited a preference and more positive affect whilst interacting and rating the robot we designed as needy. This experiment leads us to the conclusion that our architecture and setup succeeded in eliciting positive and caregiving behavior from adults of different age groups and technological background. Finally, the consistency and reactivity of the robot during this dyadic interaction appeared crucial for the enjoyment and engagement of the human partner.Peer reviewe

Towards a model of emotion expression in an interactive robot head

In this paper we present a robotic head designed for interaction with humans, endowed with mechanisms to make the robot respond to social interaction with emotional expressions, allowing the emotional expression of the robot to be directly influenced by the social interaction process. We look into how emotionally expressive visual feedback from the robot can enrich the interaction process and provide the participant with additional information regarding the interaction, allowing the user to better understand the intentions of the robot. We discuss some of the interactions that are possible with ERWIN and how this can effect the response of the system. We show experimental scenarios where the interaction processes influences the emotional expressions and how the participants interpret this. We draw our conclusions from the feedback from experiments, showing that indeed emotional expression can have an influence on the social interaction between a robot and human</p

Socio-emotional development in high functioning children with autism spectrum disorders using a humanoid robot

The use of robots had already been proven to encourage the promotion of social interaction and skills lacking in children with Autism Spectrum Disorders (ASD), who typically have difficulties in recognizing facial expressions and emotions. The main goal of this research is to study the influence of a humanoid robot to develop socio-emotional skills in children with ASD. The children’s performance in game scenarios aiming to develop facial expressions recognition skills is presented. Along the sessions, children who performed the game scenarios with the robot and the experimenter had a significantly better performance than the children who performed the game scenarios without the robot. The main conclusions of this research support that a humanoid robot is a useful tool to develop socio-emotional skills in the intervention of children with ASD, due to the engagement and positive learning outcome observed.CIEd & Algoritm