An architecture for sensate robots : real time social-gesture recognition using a full body array of touch sensors

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references.Touch plays a central role in social expression but, so far, research into social touch behaviors for robots has been almost. non-existent. Embodied machines have the unique capability to sense human body language, which will enable robots to better comprehend, anticipate and respond to their human companions in a natural way.This thesis addresses the novel field of sensate touch by (1) creating the first. robot with full Body sensate touch and with on-screen visualization, (2) establishing a library of salient social gestures through behavioral studies, (3) implementing a first-pass touch gesture recognition system in real-time, an(d (4) running a small pilot study with children to evaluate classifications and test the device's acceptance/utility with humans. Such research is critical path to conceiving and advancing thee use of machine touch to better integrate robots in.to human social environments.All of the above will be incorporated into the huggable robotic teddy bear at the MIT Media Lab's Personal Robotics group and makes use of the Sensitive Skins circuit design created in Dan Stiehl's Masters thesis. This implementation substantially reduces his proposed total sensor numbers and type, modularizes sensors into two uniform shapes, and extends his valuable work on a single body sections to an evaluation of sensors over the entire surface of the robot.Heather-Marie Callanan Knight.M.Eng

The Grenoble System for the Social Touch Challenge at ICMI 2015

International audienceNew technologies and especially robotics is going towards more natural user interfaces. Works have been done in different modality of interaction such as sight (visual computing), and audio (speech and audio recognition) but some other modalities are still less researched. The touch modality is one of the less studied in HRI but could be valuable for naturalistic interaction. However touch signals can vary in semantics. It is therefore necessary to be able to recognize touch gestures in order to make human-robot interaction even more natural.We propose a method to recognize touch gestures. This method was developed on the CoST corpus and then directly applied on the HAART dataset as a participation of the Social Touch Challenge at ICMI 2015.Our touch gesture recognition process is detailed in this article to make it reproducible by other research teams.Besides features set description, we manually filtered the training corpus to produce 2 datasets.For the challenge, we submitted 6 different systems.A Support Vector Machine and a Random Forest classifiers for the HAART dataset.For the CoST dataset, the same classifiers are tested in two conditions: using all or filtered training datasets.As reported by organizers, our systems have the best correct rate in this year's challenge (70.91% on HAART, 61.34% on CoST).Our performances are slightly better that other participants but stay under previous reported state-of-the-art results

A First Step toward the Automatic Understanding of Social Touch for Naturalistic Human–Robot Interaction

Social robots should be able to automatically understand and respond to human touch. The meaning of touch does not only depend on the form of touch but also on the context in which the touch takes place. To gain more insight into the factors that are relevant to interpret the meaning of touch within a social context we elicited touch behaviors by letting participants interact with a robot pet companion in the context of different affective scenarios. In a contextualized lab setting, participants (n = 31) acted as if they were coming home in different emotional states (i.e., stressed, depressed, relaxed, and excited) without being given specific instructions on the kinds of behaviors that they should display. Based on video footage of the interactions and interviews we explored the use of touch behaviors, the expressed social messages, and the expected robot pet responses. Results show that emotional state influenced the social messages that were communicated to the robot pet as well as the expected responses. Furthermore, it was found that multimodal cues were used to communicate with the robot pet, that is, participants often talked to the robot pet while touching it and making eye contact. Additionally, the findings of this study indicate that the categorization of touch behaviors into discrete touch gesture categories based on dictionary definitions is not a suitable approach to capture the complex nature of touch behaviors in less controlled settings. These findings can inform the design of a behavioral model for robot pet companions and future directions to interpret touch behaviors in less controlled settings are discussed

Grasp recognition as a user interface

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.Includes bibliographical references (p. [85]-87).The Graspables project is an exploration of how measuring the way people hold and manipulate objects can be used as a user interface. As computational power continues to implemented in more and more objects and devices, new interaction methods need to be developed. The Graspables System is embodied by a physical set of sensors combined with pattern recognition software that can determine how users hold a device. The Graspables System has been implemented in two prototypes, the Bar of Soap and the Ball of Soap. User studies have been conducted demostrating the effectiveness of the Graspables System and a variety of applications have been developed to demonstrate its utility.Brandon Thomas Taylor.S.M

Socially intelligent robots that understand and respond to human touch

Touch is an important nonverbal form of interpersonal interaction which is used to communicate emotions and other social messages. As interactions with social robots are likely to become more common in the near future these robots should also be able to engage in tactile interaction with humans. Therefore, the aim of the research presented in this dissertation is to work towards socially intelligent robots that can understand and respond to human touch. To become a socially intelligent actor a robot must be able to sense, classify and interpret human touch and respond to this in an appropriate manner. To this end we present work that addresses different parts of this interaction cycle. The contributions of this dissertation are the following. We have made a touch gesture dataset available to the research community and have presented benchmark results. Furthermore, we have sparked interest into the new field of social touch recognition by organizing a machine learning challenge and have pinpointed directions for further research. Also, we have exposed potential difficulties for the recognition of social touch in more naturalistic settings. Moreover, the findings presented in this dissertation can help to inform the design of a behavioral model for robot pet companions that can understand and respond to human touch. Additionally, we have focused on the requirements for tactile interaction with robot pets for health care applications

Physical sketching tools and techniques for customized sensate surfaces

Sensate surfaces are a promising avenue for enhancing human interaction with digital systems due to their inherent intuitiveness and natural user interface. Recent technological advancements have enabled sensate surfaces to surpass the constraints of conventional touchscreens by integrating them into everyday objects, creating interactive interfaces that can detect various inputs such as touch, pressure, and gestures. This allows for more natural and intuitive control of digital systems. However, prototyping interactive surfaces that are customized to users' requirements using conventional techniques remains technically challenging due to limitations in accommodating complex geometric shapes and varying sizes. Furthermore, it is crucial to consider the context in which customized surfaces are utilized, as relocating them to fabrication labs may lead to the loss of their original design context. Additionally, prototyping high-resolution sensate surfaces presents challenges due to the complex signal processing requirements involved. This thesis investigates the design and fabrication of customized sensate surfaces that meet the diverse requirements of different users and contexts. The research aims to develop novel tools and techniques that overcome the technical limitations of current methods and enable the creation of sensate surfaces that enhance human interaction with digital systems.Sensorische Oberflächen sind aufgrund ihrer inhärenten Intuitivität und natürlichen Benutzeroberfläche ein vielversprechender Ansatz, um die menschliche Interaktionmit digitalen Systemen zu verbessern. Die jüngsten technologischen Fortschritte haben es ermöglicht, dass sensorische Oberflächen die Beschränkungen herkömmlicher Touchscreens überwinden, indem sie in Alltagsgegenstände integriert werden und interaktive Schnittstellen schaffen, die diverse Eingaben wie Berührung, Druck, oder Gesten erkennen können. Dies ermöglicht eine natürlichere und intuitivere Steuerung von digitalen Systemen. Das Prototyping interaktiver Oberflächen, die mit herkömmlichen Techniken an die Bedürfnisse der Nutzer angepasst werden, bleibt jedoch eine technische Herausforderung, da komplexe geometrische Formen und variierende Größen nur begrenzt berücksichtigt werden können. Darüber hinaus ist es von entscheidender Bedeutung, den Kontext, in dem diese individuell angepassten Oberflächen verwendet werden, zu berücksichtigen, da eine Verlagerung in Fabrikations-Laboratorien zum Verlust ihres ursprünglichen Designkontextes führen kann. Zudem stellt das Prototyping hochauflösender sensorischer Oberflächen aufgrund der komplexen Anforderungen an die Signalverarbeitung eine Herausforderung dar. Diese Arbeit erforscht dasDesign und die Fabrikation individuell angepasster sensorischer Oberflächen, die den diversen Anforderungen unterschiedlicher Nutzer und Kontexte gerecht werden. Die Forschung zielt darauf ab, neuartigeWerkzeuge und Techniken zu entwickeln, die die technischen Beschränkungen derzeitigerMethoden überwinden und die Erstellung von sensorischen Oberflächen ermöglichen, die die menschliche Interaktion mit digitalen Systemen verbessern

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

Building a semi-autonomous sociable robot platform for robust interpersonal telecommunication

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 73-74).This thesis presents the design of a software platform for the Huggable project. The Huggable is a new kind of robotic companion being developed at the MIT Media Lab for health care, education, entertainment and social communication applications. This work focuses on the social communication application as it pertains to using a semi-autonomous robotic avatar in a remote environment. The software platform consists of an extensible and robust distributed software system that connects a remote human puppeteer to the Huggable robot via internet. The paper discusses design decisions made in building the software platform and describes the technologies created for the social communication application. An informal trial of the system reveals how the system's puppeteering interface can be improved, and pinpoints where performance enhancements are needed for this particular application.by Robert Lopez Toscano.M.Eng

Lovotics: Love + Robotics, Sentimental Robot With Affective Artificial Intelligence

Ph.DDOCTOR OF PHILOSOPH