How Expressiveness of a Robotic Tutor is Perceived by Children in a Learning Environment

We present a study investigating the expressiveness of two different types of robots in a tutoring task. The robots used were i) the EMYS robot, with facial expression capabilities, and ii) the NAO robot, without facial expressions but able to perform expressive gestures. Preliminary results show that the NAO robot was perceived to be more friendly, pleasant and empathic than the EMYS robot as a tutor in a learning environment

The interaction between voice and appearance in the embodiment of a robot tutor

Robot embodiment is, by its very nature, holistic and understanding how various aspects contribute to the user perception of the robot is non-trivial. A study is presented here that investigates whether there is an interaction effect between voice and other aspects of embodiment, such as movement and appearance, in a pedagogical setting. An on-line study was distributed to children aged 11–17 that uses a modified Godspeed questionnaire. We show an interaction effect between the robot embodiment and voice in terms of perceived lifelikeness of the robot. Politeness is a key strategy used in learning and teaching, and here an effect is also observed for perceived politeness. Interestingly, participants’ overall preference was for embodiment combinations that are deemed polite and more like a teacher, but are not necessarily the most lifelike. From these findings, we are able to inform the design of robotic tutors going forward

Child–robot relationship formation: A narrative review of empirical research

This narrative review aimed to elucidate which robot-related characteristics predict relationship formation between typically-developing children and social robots in terms of closeness and trust. Moreover, we wanted to know to what extent relationship formation can be explained by children’s experiential and cognitive states during interaction with a robot. We reviewed 86 journal articles and conference proceedings published between 2000 and 2017. In terms of predictors, robots’ responsiveness and role, as well as strategic and emotional interaction between robot and child, increased closeness between the child and the robot. Findings about whether robot features predict children’s trust in robots were inconsistent. In terms of children’s experiential and cognitive states during interaction with a robot, robot characteristics and interaction styles were associated with two experiential states: engagement and enjoyment/liking. The literature hardly addressed the impact of experiential and cognitive states on closeness and trust. Comparisons of children’s interactions with robots, adults, and objects showed that robots are perceived as neither animate nor inanimate, and that they are entities with whom children will likely form social relationships. Younger children experienced more enjoyment, were less sensitive to a robot’s interaction style, and were more prone to anthropomorphic tendencies and effects than older children. Tailoring a robot’s sex to that of a child mainly appealed to boys

A Systematic Review of Adaptivity in Human-Robot Interaction

As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains

An emotion and memory model for social robots : a long-term interaction

In this thesis, we investigate the role of emotions and memory in social robotic companions. In particular, our aim is to study the effect of an emotion and memory model towards sustaining engagement and promoting learning in a long-term interaction. Our Emotion and Memory model was based on how humans create memory under various emotional events/states. The model enabled the robot to create a memory account of user's emotional events during a long-term child-robot interaction. The robot later adapted its behaviour through employing the developed memory in the following interactions with the users. The model also had an autonomous decision-making mechanism based on reinforcement learning to select behaviour according to the user preference measured through user's engagement and learning during the task. The model was implemented on the NAO robot in two different educational setups. Firstly, to promote user's vocabulary learning and secondly, to inform how to calculate area and perimeter of regular and irregular shapes. We also conducted multiple long-term evaluations of our model with children at the primary schools to verify its impact on their social engagement and learning. Our results showed that the behaviour generated based on our model was able to sustain social engagement. Additionally, it also helped children to improve their learning. Overall, the results highlighted the benefits of incorporating memory during child-Robot Interaction for extended periods of time. It promoted personalisation and reflected towards creating a child-robot social relationship in a long-term interaction

A motivational approach to support healthy habits in long-term child–robot interaction

We examine the use of role-switching as an intrinsic motivational mechanism to increase engagement in long-term child–robot interaction. The present study describes a learning framework where children between 9 and 11-years-old interact with a robot to improve their knowledge and habits with regards to healthy life-styles. Experiments were carried out in Italy where 41 children were divided in three groups interacting with: (i) a robot with a role-switching mechanism, (ii) a robot without a role-switching mechanism and (iii) an interactive video. Additionally, a control group composed of 43 more children, who were not exposed to any interactive approach, was used as a baseline of the study. During the intervention period, the three groups were exposed to three interactive sessions once a week. The aim of the study was to find any difference in healthy-habits acquisition based on alternative interactive systems, and to evaluate the effectiveness of the role-switch approach as a trigger for engagement and motivation while interacting with a robot. The results provide evidence that the rate of children adopting healthy habits during the intervention period was higher for those interacting with a robot. Moreover, alignment with the robot behaviour and achievement of higher engagement levels were also observed for those children interacting with the robot that used the role-switching mechanism. This supports the notion that role-switching facilitates sustained long-interactions between a child and a robot

Acoustic-based Smart Tactile Sensing in Social Robots

Mención Internacional en el título de doctorEl sentido del tacto es un componente crucial de la interacción social humana y es único entre los cinco sentidos. Como único sentido proximal, el tacto requiere un contacto físico cercano o directo para registrar la información. Este hecho convierte al tacto en una modalidad de interacción llena de posibilidades en cuanto a comunicación social. A través del tacto, podemos conocer la intención de la otra persona y comunicar emociones. De esta idea surge el concepto de social touch o tacto social como el acto de tocar a otra persona en un contexto social. Puede servir para diversos fines, como saludar, mostrar afecto, persuadir y regular el bienestar emocional y físico. Recientemente, el número de personas que interactúan con sistemas y agentes artificiales ha aumentado, principalmente debido al auge de los dispositivos tecnológicos, como los smartphones o los altavoces inteligentes. A pesar del auge de estos dispositivos, sus capacidades de interacción son limitadas. Para paliar este problema, los recientes avances en robótica social han mejorado las posibilidades de interacción para que los agentes funcionen de forma más fluida y sean más útiles. En este sentido, los robots sociales están diseñados para facilitar interacciones naturales entre humanos y agentes artificiales. El sentido del tacto en este contexto se revela como un vehículo natural que puede mejorar la Human-Robot Interaction (HRI) debido a su relevancia comunicativa en entornos sociales. Además de esto, para un robot social, la relación entre el tacto social y su aspecto es directa, al disponer de un cuerpo físico para aplicar o recibir toques. Desde un punto de vista técnico, los sistemas de detección táctil han sido objeto recientemente de nuevas investigaciones, sobre todo dedicado a comprender este sentido para crear sistemas inteligentes que puedan mejorar la vida de las personas. En este punto, los robots sociales se han convertido en dispositivos muy populares que incluyen tecnologías para la detección táctil. Esto está motivado por el hecho de que un robot puede esperada o inesperadamente tener contacto físico con una persona, lo que puede mejorar o interferir en la ejecución de sus comportamientos. Por tanto, el sentido del tacto se antoja necesario para el desarrollo de aplicaciones robóticas. Algunos métodos incluyen el reconocimiento de gestos táctiles, aunque a menudo exigen importantes despliegues de hardware que requieren de múltiples sensores. Además, la fiabilidad de estas tecnologías de detección es limitada, ya que la mayoría de ellas siguen teniendo problemas tales como falsos positivos o tasas de reconocimiento bajas. La detección acústica, en este sentido, puede proporcionar un conjunto de características capaces de paliar las deficiencias anteriores. A pesar de que se trata de una tecnología utilizada en diversos campos de investigación, aún no se ha integrado en la interacción táctil entre humanos y robots. Por ello, en este trabajo proponemos el sistema Acoustic Touch Recognition (ATR), un sistema inteligente de detección táctil (smart tactile sensing system) basado en la detección acústica y diseñado para mejorar la interacción social humano-robot. Nuestro sistema está desarrollado para clasificar gestos táctiles y localizar su origen. Además de esto, se ha integrado en plataformas robóticas sociales y se ha probado en aplicaciones reales con éxito. Nuestra propuesta se ha enfocado desde dos puntos de vista: uno técnico y otro relacionado con el tacto social. Por un lado, la propuesta tiene una motivación técnica centrada en conseguir un sistema táctil rentable, modular y portátil. Para ello, en este trabajo se ha explorado el campo de las tecnologías de detección táctil, los sistemas inteligentes de detección táctil y su aplicación en HRI. Por otro lado, parte de la investigación se centra en el impacto afectivo del tacto social durante la interacción humano-robot, lo que ha dado lugar a dos estudios que exploran esta idea.The sense of touch is a crucial component of human social interaction and is unique among the five senses. As the only proximal sense, touch requires close or direct physical contact to register information. This fact makes touch an interaction modality full of possibilities regarding social communication. Through touch, we are able to ascertain the other person’s intention and communicate emotions. From this idea emerges the concept of social touch as the act of touching another person in a social context. It can serve various purposes, such as greeting, showing affection, persuasion, and regulating emotional and physical well-being. Recently, the number of people interacting with artificial systems and agents has increased, mainly due to the rise of technological devices, such as smartphones or smart speakers. Still, these devices are limited in their interaction capabilities. To deal with this issue, recent developments in social robotics have improved the interaction possibilities to make agents more seamless and useful. In this sense, social robots are designed to facilitate natural interactions between humans and artificial agents. In this context, the sense of touch is revealed as a natural interaction vehicle that can improve HRI due to its communicative relevance. Moreover, for a social robot, the relationship between social touch and its embodiment is direct, having a physical body to apply or receive touches. From a technical standpoint, tactile sensing systems have recently been the subject of further research, mostly devoted to comprehending this sense to create intelligent systems that can improve people’s lives. Currently, social robots are popular devices that include technologies for touch sensing. This is motivated by the fact that robots may encounter expected or unexpected physical contact with humans, which can either enhance or interfere with the execution of their behaviours. There is, therefore, a need to detect human touch in robot applications. Some methods even include touch-gesture recognition, although they often require significant hardware deployments primarily that require multiple sensors. Additionally, the dependability of those sensing technologies is constrained because the majority of them still struggle with issues like false positives or poor recognition rates. Acoustic sensing, in this sense, can provide a set of features that can alleviate the aforementioned shortcomings. Even though it is a technology that has been utilised in various research fields, it has yet to be integrated into human-robot touch interaction. Therefore, in thiswork,we propose theATRsystem, a smart tactile sensing system based on acoustic sensing designed to improve human-robot social interaction. Our system is developed to classify touch gestures and locate their source. It is also integrated into real social robotic platforms and tested in real-world applications. Our proposal is approached from two standpoints, one technical and the other related to social touch. Firstly, the technical motivation of thiswork centred on achieving a cost-efficient, modular and portable tactile system. For that, we explore the fields of touch sensing technologies, smart tactile sensing systems and their application in HRI. On the other hand, part of the research is centred around the affective impact of touch during human-robot interaction, resulting in two studies exploring this idea.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Pedro Manuel Urbano de Almeida Lima.- Secretaria: María Dolores Blanco Rojas.- Vocal: Antonio Fernández Caballer

Adaptive human-robot interaction in sensorimotor task instruction: From human to robot dance tutors

Den generella tilliten har i Sverige länge varit stabil och anses ur ett internationellt perspektiv vara unik. Syftet med denna studie är att studera om det finns ett samband mellan generell tillit och xenofobi. På grund av den minskade toleransen till främlingar under de senaste åren, studeras även hur generell den svenska tilliten egentligen är, eller om den generella tilliten är beroende av gruppspecifik tillit. Studien grundar sig på Robert Putnams teori om socialt kapital samt tidigare forskning som visat på sambandet mellan generell tillit och xenofobi. Studien använder sig av data från World Value Survey och behandlar svensk data från 2011. Studiens frågeställningar har besvarats genom en logistisk regressionsanalys. Resultaten visade ett positivt samband mellan låg in-gruppstillit och xenofobi samt ett positivt samband mellan låg ut-gruppstillit och xenofobi. Slutsatsen blev att det fanns ett samband mellan generell tillit och xenofobi. Detta samband kunde även till viss del förklaras av gruppspecifik tillit, där särskilt tillit till individer från andra kulturella sfärer än den egna var av betydelse