Collaborative Robots and Tangled Passages of Tactile-Affects

Collaborative robots are increasingly entering industrial contexts and workflows. These contexts are not just locations for production, they are vibrant social and sensory environments. For better or for worse their entry brings potential to reorganize established tactile and affective dynamics that encompass production processes. There is still much to be learned about these highly contextual and complex dynamics in HRI research and the design of industrial robotics; common approaches in industrial collaborative robotics are restricted to evaluating ‘effective interface design’ whereas methods that seek to measure ‘affective touch’ have limited application to these industrial domains. This paper offers an extended analytical framework and methodological approach to deepen understandings of affect and touch beyond emotional responses to direct human-robot interactions. These distinct contributions are grounded in fieldwork in a glass factory with newly installed collaborative robots. They are illustrated through an ethnographic narrative that traces the emergence and circulation of affect, across material, experiential and social planes. Beyond this single case ‘tangled passages of tactile-affects’ is offered as novel and valuable concept, that is distinct from the notion of ‘affective touch’, and holds potential to generate holistic and nuanced understandings of how human experiences can be affected by the introduction of new robots in ‘the wild’

On the Relationship between People, Objects, & Interactive Technologies: Transforming Digital & Physical experiences through the process of Realizing Empathy

La manera com les persones es relacionen amb el seu entorn, ja sigui físic o digital, és cada cop més complexa i fugaç, fent que la relació de l'usuari amb els seus objectes i eines digitals, de vegades, sigui extrema i de curta durada. Tanmateix, la propietat d'objectes i objectes tecnològics interactius no és buida de significat, són mostres de reflexió i representació per als altres i del seu paper a la societat. La clau per mantenir una relació i el significat amb aquests objectes rau en el disseny i la intenció de l'experiència interactiva creada. Inspirats en les disciplines de la psicologia, el procés de disseny, la interacció humà-ordinador i els models de negoci, aquesta tesi explora, analitza, crea i prova els fonaments teòrics sobre l'empatia i el concepte d'entaular una relació de llarga durada entre les persones i les tecnologies interactives.  Amb aquesta finalitat, aquesta tesi es divideix en 4 fases: (1) l’estudi en profunditat de les referències bibliogràfiques dins del sector HCI, amb especial atenció al rol del disseny i la psicologia amb la intenció de respondre preguntes com: “Com podem construir relacions de llarga durada entre persones i objectes intel·ligents?” (2) Recopilar i adoptar definicions, eines i terminologia de treballs relacionats que aportin a la construcció de la contribució principal d'aquesta tesi, (3) Crear i presentar un model d'interacció entre persones i tecnologia que aporti a una interacció de llarga durada, i (4) presentar un cas d’estudi on s’implementi el model proposat.  Després del treball bibliogràfic, al sector de l'HCI, s'ha identificat un buit, fruit de les principals preocupacions expressades: la manca de connexió entre la teoria i la pràctica del disseny, així com una mancança en l’àmbit de l'Empatia. El resultat fa que molts dels models d’interacció amb intenció empàtica i afectiva no se sustentin entre si. Això ens ha portat a la segona fase de la tesi on aprofitem les referències de múltiples disciplines per estudiar què és l'empatia, com s'implementa, com es percep i com evoluciona cap a l'objectiu d'una relació a llarg termini, com a punt focal cap a les principals contribucions de la tesi. .  Després de reunir i analitzar exhaustivament les referències al voltant de l'empatia, entrem a la tercera fase on presentem el model teòric d'interacció amb el potencial d'establir una interacció a llarg termini i l’anomenat Procés de realització de l'empatia (RE). Més que intentar definir què és l'empatia, aquesta proposta intenta oferir una perspectiva diferent de l'empatia i visualitza el seu abast com un procés influenciat per models de diàleg i col·laboració amb el propòsit de crear comprensió mútua i donar significat a aquest intercanvi.  Amb un model clar i una sòlida base teòrica, la fase final de la tesi cerca provar el model proposat amb l'objectiu d'observar si es poden detectar indicadors d'afecció afectiva i confiança entre una persona i el seu objecte tecnològic. En aquest cas, vam tenir l'oportunitat de treballar amb robots socials com el nostre “altre actor” per dissenyar les proves del model. Aquestes proves pretenien capturar els indicadors d'empatia entre un humà i un robot que abraça: l'aferrament afectiu, la confiança, la regulació de les expectatives i la reflexió sobre la perspectiva de l'altre dins un conjunt d'estratègies de col·laboració. Plantegem la hipòtesi que una estratègia de col·laboració activa condueix a un compromís més significatiu de generar empatia entre un humà i un robot en comparació amb una estratègia passiva. Els resultats són encoratjadors i clarament estableixen un camí per a futures investigacions sobre el disseny d'aquest model. La forma en que las personas se relacionan con su entorno, ya sea físico o digital, se vuelve cada vez más compleja y fugaz, haciendo que la relación del usuario con sus objetos y herramientas digitales, en ocasiones, sea extrema y de corta duración. Sin embargo, la propiedad de objetos y objetos tecnológicos interactivos no es vacía de significado, son muestras de reflexión y representación para los demás y de su papel en la sociedad. La clave para mantener una relación y significado con estos objetos radica en el diseño y la intención de la experiencia interactiva creada. Inspirados en las disciplinas de la psicología, el proceso de diseño, la interacción humano-ordenador y los modelos de negocio, esta tesis explora, analiza, crea y prueba los fundamentos teóricos sobre la empatía y el concepto de entablar una relación de larga duración entre las personas y las tecnologías interactivas.  Con este fin, esta tesis se divide en 4 fases: (1) estudio en profundidad de las referencias bibliográficas dentro del sector HCI, con especial atención al rol del diseño y la psicología con la intención de responder a preguntas como: “¿Cómo podemos construir relaciones de larga duración entre personas y objetos inteligentes?”(2) Recopilar y adoptar definiciones, herramientas y terminología de trabajos relacionados que aporten a la construcción de la contribución principal de esta tesis, (3) Crear y presentar un modelo de interacción entre personas y tecnología que aporte a una interacción de larga duración, y (4) presentar un caso de estudio donde se implemente el modelo propuesto.  Tras el trabajo bibliográfico en el sector del HCI se ha identificado un vacío, fruto de las principales preocupaciones expresadas: la falta de conexión entre la teoría y la práctica del diseño, así como una falta en el tema de la Empatía. El resultado hace que muchos de los modelos de interacción con intención empática y afectiva no se sustenten entre sí. Esto nos ha llevado a la segunda fase de la tesis en la que aprovechamos las referencias de múltiples disciplinas para estudiar qué es la empatía, cómo se implementa, cómo se percibe y cómo evoluciona hacia el objetivo de una relación a largo plazo, como punto focal hacia las principales contribuciones de la tesis. .  Después de una reunir y analizar exhaustivamente las referencias en torno a la empatía, entramos en la tercera fase donde presentamos el modelo teórico de interacción con el potencial de entablar una interacción a largo plazo y denominado Proceso de realización de la empatía (RE). Más que intentar definir qué es la empatía, esta propuesta trata de ofrecer una perspectiva diferente a la empatía y visualiza su alcance como un proceso influenciado por modelos de diálogo y colaboración con el propósito de crear comprensión mutua y dar significado a ese intercambio.  Con un modelo claro y una sólida base teórica, la fase final de la tesis busca probar el modelo propuesto con el objetivo de observar si el modelo puede detectar indicadores de Apego Afectivo y Confianza entre una persona y su objeto tecnológico. En el caso de este trabajo, tuvimos la oportunidad de trabajar con robots sociales como nuestro “otro actor” para diseñar las pruebas del modelo. Estas pruebas pretendían capturar los indicadores de de empatía entre un humano y un robot que abarca: el apego afectivo, la confianza, la regulación de las expectativas y la reflexión sobre la perspectiva del otro dentro de un conjunto de estrategias de colaboración. Planteamos la hipótesis de que una estrategia de colaboración activa conduce a un compromiso más significativo de generar empatía entre un humano y un robot en comparación con una estrategia pasiva. Los resultados son alentadores y claramente establecen un camino para futuras investigaciones sobre el diseño de este modelo. How people engage with their surroundings, whether physical or digital, becomes increasingly complex and rapid, making the user’s relationship with their objects and digital tools, at times, extreme and short-lived. Yet, there is still meaning in ownership of objects and interactive technological objects, they are tokens of reflection and representation to others and their role in society. The key to sustaining a relationship and sense of meaning with these objects lies in the design and intention of the interactive experience created. Inspired by disciplines of psychology, design, Human-computer interaction, and business modeling, this thesis explored, analyzed, created, and tested theoretical foundations on Empathy and the concept of initiating a long-term relationship between people and their interactive technologies.  To that end, the thesis book was managed in 4 main stages: (1) presenting a deeper dive into bibliographic references within HCI and the role of both design and psychology in the attempt to tackle questions like: “How can we build long-term relationships between people and their smart objects?” (2) Collect and adopt from related works that helped build the main contributions of the thesis book, (3) Create an interaction model between humans and their technology that lent itself for potential long-term engagement, and (4) a case study that implemented and instantiated the model designed.     After mapping the HCI bibliographical works in the first phase, a gap was revealed indicative of the main concerns expressed: a lack of connection between theory and design practice as well as a lack in the topic of Empathy. The result makes many of the models of interaction with empathetic and affective intention unsupported between each other. This has led us to the second phase of the thesis where we leveraged references across multiple disciplines to survey what empathy is, how it is implemented, perceived and evolved toward the goal of long-term relationship, as a focal point toward the main thesis contributions.   After an exhaustive gathering and analysis of the work around Empathy, we entered the third phase where we present the proposed theoretical model of interaction with the potential for long-term engagement named the Process of Realizing Empathy (RE). Rather than attempting to further define empathy, this proposal is about offering a different perspective to empathy that visualizes its scope as a process influenced by dialogue and collaborative models with the goal to reach meaning between the actors involved.  With a clear model in place and a strong theoretical foundation, the final phase of the thesis looked to test the proposed model with the goal of observing if the model can provoke its indicators of Affective Attachment and Trust between a person and their technological object. In the case of this thesis work, we had the opportunity to work with social robots as our “other actor” to design the tests for the model. This testbed meant to capture the indicators of early empathy realization between a human and a robot encompassing affective attachment, trust, expectation regulation, and reflecting on the other’s perspective within a set of collaborative strategies. We hypothesized that an active collaboration strategy is conducive to a more meaningful and purposeful engagement of realizing empathy between a human and a robot compared to a passive one. The results are encouraging and clearly establish a path for further research on this model’s design.

Building Long-Term Human–Robot Relationships: Examining Disclosure, Perception and Well-Being Across Time

While interactions with social robots are novel and exciting for many people, one concern is the extent to which people’s behavioural and emotional engagement might be sustained across time, since during initial interactions with a robot, its novelty is especially salient. This challenge is particularly noteworthy when considering interactions designed to support people’s well-being, with limited evidence (or empirical exploration) of social robots’ capacity to support people’s emotional health over time. Accordingly, our aim here was to examine how long-term repeated interactions with a social robot affect people’s self-disclosure behaviour toward the robot, their perceptions of the robot, and how such sustained interactions influence factors related to well-being. We conducted a mediated long-term online experiment with participants conversing with thesocial robot Pepper 10 times over 5 weeks. We found that people self-disclose increasingly more to a social robot over time, and report the robot to be more social and competent over time. Participants’ moods also improved after talking to the robot, and across sessions, they found the robot’s responses increasingly comforting as well as reported feeling less lonely. Finally, our results emphasize that when the discussion frame was supposedly more emotional (in this case, framing questions in the context of the COVID-19 pandemic), participants reported feeling lonelier and more stressed. These results set the stage forsituating social robots as conversational partners and provide crucial evidence for their potential inclusion in interventions supporting people’s emotional health through encouraging self-disclosure

A Study of Non-Linguistic Utterances for Social Human-Robot Interaction

The world of animation has painted an inspiring image of what the robots of the future could be. Taking the robots R2D2 and C3PO from the Star Wars films as representative examples, these robots are portrayed as being more than just machines, rather, they are presented as intelligent and capable social peers, exhibiting many of the traits that people have also. These robots have the ability to interact with people, understand us, and even relate to us in very personal ways through a wide repertoire of social cues. As robotic technologies continue to make their way into society at large, there is a growing trend toward making social robots. The field of Human-Robot Interaction concerns itself with studying, developing and realising these socially capable machines, equipping them with a very rich variety of capabilities that allow them to interact with people in natural and intuitive ways, ranging from the use of natural language, body language and facial gestures, to more unique ways such as expression through colours and abstract sounds. This thesis studies the use of abstract, expressive sounds, like those used iconically by the robot R2D2. These are termed Non-Linguistic Utterances (NLUs) and are a means of communication which has a rich history in film and animation. However, very little is understood about how such expressive sounds may be utilised by social robots, and how people respond to these. This work presents a series of experiments aimed at understanding how NLUs can be utilised by a social robot in order to convey affective meaning to people both young and old, and what factors impact on the production and perception of NLUs. Firstly, it is shown that not all robots should use NLUs. The morphology of the robot matters. People perceive NLUs differently across different robots, and not always in a desired manner. Next it is shown that people readily project affective meaning onto NLUs though not in a coherent manner. Furthermore, people's affective inferences are not subtle, rather they are drawn to well established, basic affect prototypes. Moreover, it is shown that the valence of the situation in which an NLU is made, overrides the initial valence of the NLU itself: situational context biases how people perceive utterances made by a robot, and through this, coherence between people in their affective inferences is found to increase. Finally, it is uncovered that NLUs are best not used as a replacement to natural language (as they are by R2D2), rather, people show a preference for them being used alongside natural language where they can play a supportive role by providing essential social cues

Towards a Cognitive Architecture for Socially Adaptive Human-Robot Interaction

People have a natural predisposition to interact in an adaptive manner with others, by instinctively changing their actions, tones and speech according to the perceived needs of their peers. Moreover, we are not only capable of registering the affective and cognitive state of our partners, but over a prolonged period of interaction we also learn which behaviours are the most appropriate and well-suited for each one of them individually. This universal trait that we share regardless of our different personalities is referred to as social adaptation (adaptability). Humans are always capable of adapting to the others although our personalities may influence the speed and efficacy of the adaptation. This means that in our everyday lives we are accustomed to partake in complex and personalized interactions with our peers. Carrying this ability to personalize to human-robot interaction (HRI) is highly desirable since it would provide user-personalized interaction, a crucial element in many HRI scenarios - interactions with older adults, assistive or rehabilitative robotics, child-robot interaction (CRI), and many others. For a social robot to be able to recreate this same kind of rich, human-like interaction, it should be aware of our needs and affective states and be capable of continuously adapting its behaviour to them. Equipping a robot with these functionalities however is not a straightforward task. A robust approach for solving this is implementing a framework for the robot supporting social awareness and adaptation. In other words, the robot needs to be equipped with the basic cognitive functionalities, which would allow the robot to learn how to select the behaviours that would maximize the pleasantness of the interaction for its peers, while being guided by an internal motivation system that would provide autonomy to its decision-making process. The goal of this research was threefold: attempt to design a cognitive architecture supporting social HRI and implement it on a robotic platform; study how an adaptive framework of this kind would function when tested in HRI studies with users; and explore how including the element of adaptability and personalization in a cognitive framework would in reality affect the users - would it bring an additional richness to the human-robot interaction as hypothesized, or would it instead only add uncertainty and unpredictability that would not be accepted by the robot`s human peers? This thesis covers the work done on developing a cognitive framework for human-robot interaction; analyzes the various challenges of implementing the cognitive functionalities, porting the framework on several robotic platforms and testing potential validation scenarios; and finally presents the user studies performed with the robotic platforms of iCub and MiRo, focused on understanding how a cognitive framework behaves in a free-form HRI context and if humans can be aware and appreciate the adaptivity of the robot. In summary, this thesis had the task of approaching the complex field of cognitive HRI and attempt to shed some light on how cognition and adaptation develop from both the human and the robot side in an HRI scenario

Robotic Knitting

As a reaction to typically dead-end debates on future human and robot collaboration that tend to be either dismissive or overly welcoming towards »cobot« technologies, this book provides a technofeminist intervention. Pat Treusch not only shows how both the fields of technofeminism and robotics can engage in a practical exchange through knitting, but also contributes a tangible example of coboting dynamics. Robotic Knitting re-negotiates the boundaries between formalisation and embodiment, craft and high-tech as well as useful and dysfunctional machines. It re-crafts the nature of collaboration between human and robot. This finally entails an alternative mode of relating - a mode that enables an account of careful coboting

Real-time generation and adaptation of social companion robot behaviors

Social robots will be part of our future homes. They will assist us in everyday tasks, entertain us, and provide helpful advice. However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate. An essential skill of every social robot is verbal and non-verbal communication. In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine. Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors. In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot. However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems. This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences. Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence. The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning. Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning. It provides a higher-level view from the system designer's perspective and guidance from the start to the end. It illustrates the process of modeling, simulating, and evaluating such adaptation processes. Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness. The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes. They are evaluated in the lab and in in-situ studies. These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor. Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukünftigen Zuhauses sein. Sie werden uns bei alltäglichen Aufgaben unterstützen, uns unterhalten und uns mit hilfreichen Ratschlägen versorgen. Noch gibt es allerdings technische Herausforderungen, die zunächst überwunden werden müssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen. Eine wesentliche Fähigkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation. Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine Verkörperung, die Erwartungen an die Maschine weckt. Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natürliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen. Darüber hinaus müssen Roboter auch die individuellen Vorlieben der Benutzer berücksichtigen. So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprägt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter führt. Roboter haben jedoch keine menschliche Intuition - sie müssen mit entsprechenden Algorithmen für diese Probleme ausgestattet werden. In dieser Arbeit wird der Einsatz von bestärkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die Bedürfnisse und Vorlieben des Benutzers anzupassen. Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern. Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle über die multimodale Verhaltenserzeugung des Roboters, ein Verständnis des menschlichen Feedbacks und eine algorithmische Basis für maschinelles Lernen. Daher wird in dieser Arbeit ein konzeptioneller Rahmen für die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestärkendem Lernen entwickelt. Er bietet eine übergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende. Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse. Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten. Der konzeptionelle Rahmen wird für mehrere Anwendungsfälle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen führt, die in Labor- und In-situ-Studien evaluiert werden. Diese Ansätze befassen sich mit typischen Aktivitäten in häuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der Persönlichkeit, dem Persona, der Höflichkeit und dem Humor des Roboters liegt. In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an

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