Desarrollo de software de bajo nivel para un brazo robot portátil

Este producto forma parte del desarrollo del proyecto EXO-FA (EXOsqueleton – Flail Arm1) es un proyecto de colaboración de la Universidad Politécnica de Valencia y el Hospital Universitario La Fe. Tiene como objetivo el diseño de un brazo robótico que permita realizar tareas determinadas a personas con discapacidad motriz, provocadas por causas degenerativas o accidente.Marqués Villarroya, S. (2016). Desarrollo de software de bajo nivel para un brazo robot portátil. Universitat Politècnica de València. http://hdl.handle.net/10251/75542TFG

Arquitectura de percepción bioinspirada basada en atención para un robot social

La atención desempeña un papel fundamental, tanto para los seres humanos como para los sistemas artificiales, ya que es una habilidad crucial que nos permite interactuar de manera efectiva con nuestro entorno. Desde la infancia hasta la edad adulta, la atención nos ayuda a concentrarnos en estímulos relevantes, procesar información de manera eficiente y responder a estímulos emocionales y sociales. Además, de influir en aspectos importantes de nuestras vidas, como el aprendizaje y las interacciones sociales. La implementación de mecanismos de atención en sistemas artificiales tiene como objetivo aprovechar los beneficios de esta habilidad fundamental. Esto se traduce en una mejora en el procesamiento de información, la toma de decisiones y la interacción con el entorno. La atención en sistemas artificiales es un área de investigación en constante desarrollo, con el propósito de mejorar la capacidad de los sistemas inteligentes en diversas aplicaciones. Uno de los campos donde más se ha estudiado el concepto de la atención es en visión artificial, en la cual se utiliza para resaltar regiones relevantes en las imágenes, lo que mejora el análisis y el reconocimiento de objetos, mientras que en la robótica, la atención permite a los robots enfocarse en objetos o eventos específicos, mejorando su capacidad de reacción y ejecución de tareas. Por este motivo, en este trabajo se propone un sistema de percepción bioinspirado basado en atención diseñado para mejorar la interacción humano-robot. Este sistema está diseñado para localizar el foco de atención del robot en cada momento teniendo en cuenta la tarea actual, los estímulos disponibles y el estado interno del robot. El sistema integra fenómenos bioinspirados como la inhibición al retorno, la relocalización del foco de atención dependiendo de los estímulos, los conceptos de atención sostenida y puntual para el cambio en el foco de atención y de agregación de estímulos de forma exógena y endógena de forma independiente. Además, se ha integrado en una plataforma robótica y se ha validado su funcionamiento en diferentes aplicaciones. Este trabajo se ha abordado desde dos perspectivas: la ampliación de las capacidades perceptuales del robot y la mejora de la interacción gracias a la integración de la atención en la arquitectura software de las plataformas robóticas. Para ello, en este trabajo se han investigado los estímulos más relevantes para la atención en humanos y su integración en el ámbito de la robótica y como realizar la agregación y fusión multisensorial de estos desde un punto de vista basado en la atención, consiguiendo una representación del entorno y seleccionando la posición del foco de atención en cada momento. Por otro lado, se ha investigado la relevancia de la integración de este sistema artificial a una plataforma robótica en lo que respecta a la interacción humano-robot, lo que ha dado lugar a un estudio que explora esta idea.Attention plays a fundamental role for both humans and artificial systems, as it is a crucial skill that enables us to interact effectively with our environment. From childhood to adulthood, attention helps us to focus on relevant stimuli, process information efficiently, and respond to emotional and social stimuli. It also influences important aspects of our lives, such as learning and social interactions. The implementation of attention mechanisms in artificial systems aims to take advantage of the benefits of this fundamental ability. This translates into improved information processing, decision making and interaction with the environment. Attention in artificial systems is an area of research in constant development, with the purpose of improving the capacity of intelligent systems in various applications. The fields where the concept of attention has been most studied are computer vision and robotics. In computer vision, attention is used to highlight relevant areas in images, which improves object analysis and recognition, while in robotics, attention allows robots to focus on specific objects or events, improving their ability to react and perform tasks. For this reason, this work proposes a bio-inspired attention-based perception system designed to improve human-robot interaction. This system is designed to locate the focus of attention of the robot at each moment, taking into account the current task, the available stimuli and the internal state of the robot.Moreover, the architecture integrates bioinspired concepts such as return inhibition, stimulus-dependent relocation of the focus of attention, the concepts of sustained and punctual attention for the shift in the focus of attention and the aggregation of exogenous and endogenous stimuli independently are integrated. In addition to this, it has been integrated into a robotic platform, and its performance has been validated in different applications. This work has been approached from two perspectives: the increase of the perceptual capabilities of the robot and the improvement of the interaction thanks to the integration of attention in the software architecture of robotic platforms. To this end, in this work, we have investigated the most relevant stimuli for attention in humans and their integration in the robotics environment, and how to perform the aggregation and multisensory fusion of these from an attention-based point of view, achieving a representation of the environment and selecting the position of the focus of attention at each moment. On the other hand, we have investigated the relevance of the integration of this artificial system to a robotic platform in terms of human-robot interaction, leading to a study that explores this idea.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Antonio Fernández Caballero.- Secretario: Concepción Alicia Monje Micharet.- Vocal: Plinio Moreno Lópe

Asynchronous federated learning system for human-robot touch interaction

Artificial intelligence and robotics are advancing at an incredible pace; however, there is a risk associated with the data privacy and personal information of users interacting with these systems and platforms. In this context, the federated learning approach emerged to enable large-scale, distributed learning without the need to transmit or store any information necessary to train the learning models. In a previous paper, we presented a system capable of detecting, locating, and classifying what kind of contact occurs between humans and one of our robots using innovative contact microphone technology. In this work we go further, improving the previously presented touch system with a multi-user, multi-robot, distributed, and scalable learning approach that is able to learn in a collaborative and incremental way while respecting the privacy of the user's information. The system has been successfully evaluated in a real environment with 28 different users divided in 7 different groups. To assess the performance of our system with this federated learning approach, we compared it to the same distributed learning system without federated learning. That is, the control group for this comparison is a central node directly receiving all the training examples obtained by each robot locally. We found that in this context the inclusion of federated learning improves the results concerning traditional distributed learning.The research leading to these results has received funding from the projects: Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), RTI2018-096338-B-I00, funded by the Ministerio de Ciencia, Innovación y Universidades; Robots sociales para mitigar la soledad y el aislamiento en mayores (SOROLI), PID2021-123941OA-I00, funded by Agencia Estatal de Investigación (AEI), Spanish Ministerio de Ciencia e Innovación; the project PLEC2021-007819, funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR, and RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by the European Social Funds (FSE) of the EU. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022 )

Active learning based on computer vision and human-robot interaction for the user profiling and behavior personalization of an autonomous social robot

Social robots coexist with humans in situations where they have to exhibit proper communication skills. Since users may have different features and communicative procedures, personalizing human-robot interactions is essential for the success of these interactions. This manuscript presents Active Learning based on computer vision and human-robot interaction for user recognition and profiling to personalize robot behavior. The system identifies people using Intel-face-detection-retail-004 and FaceNet for face recognition and obtains users" information through interaction. The system aims to improve human-robot interaction by (i) using online learning to allow the robot to identify the users and (ii) retrieving users' information to fill out their profiles and adapt the robot's behavior. Since user information is necessary for adapting the robot for each interaction, we hypothesized that users would consider creating their profile by interacting with the robot more entertaining and easier than taking a survey. We validated our hypothesis with three scenarios: the participants completed their profiles using an online survey, by interacting with a dull robot, or with a cheerful robot. The results show that participants gave the cheerful robot a higher usability score (82.14/100 points), and they were more entertained while creating their profiles with the cheerful robot than in the other scenarios. Statistically significant differences in the usability were found between the scenarios using the robot and the scenario that involved the online survey. Finally, we show two scenarios in which the robot interacts with a known user and an unknown user to demonstrate how it adapts to the situation.The research leading to these results has received funding from the projects: Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), RTI2018-096338-B-I00, funded by the Spain Ministry of Science, Innovation and Universities; Robots sociales para mitigar la soledad y el aislamiento en mayores (SOROLI), PID2021-123941OA-I00, funded by Agencia Estatal de Investigación (AEI), Spain Ministry of Science and Innovation. This publication is part of the R&D&I project PLEC2021-007819 funded by MCIN/AEI/10.13039/5011000-11033 and by the European Union NextGenerationEU/PRTR

Mini: A New Social Robot for the Elderly

The unceasing aging of the population is leading to new problems in developed countries. Robots represent an opportunity to extend the period of independent living of the elderly as well as to ameliorate their economic burden and social problems. We present a new social robot, Mini, specifically designed to assist and accompany the elderly in their daily life either at home or in a nursing facility. Based on the results of several meetings with experts in this field, we have built a robot able to provide services in the areas of safety, entertainment, personal assistance and stimulation. Mini supports elders and caregivers in cognitive and mental tasks. We present the robot platform and describe the software architecture, particularly focussing on the human–robot interaction. We give in detail how the robot operates and the interrelation of the different modules of the robot in a real use case. In the last part of the paper, we evaluated how users perceive the robot. Participants reported interesting results in terms of usability, appearance, and satisfaction. This paper describes all aspects of the design and development of a new social robot that can be used by other researchers who face the multiple challenges of creating a new robotic platform for older people.The research leading to these results has received funding from the projects: Development of social robots to help seniors with cognitive impairment (ROBSEN), funded by the Ministerio de Economía y Competitividad; and Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), funded by the Ministerio de Ciencia, Innovación y Universidades.Publicad