Robobo: la siguiente generación de robot educativo

[Resumen] Las carreras universitarias de informática e ingeniería han estado utilizando robots móviles en diferentes asignaturas desde hace mucho tiempo. Hasta el momento, debido principalmente a limitaciones económicas, estos robots educativos han sido bastante simples en términos tecnológicos. Esto no era un gran problema porque la robótica no se consideraba un mercado real en la industria, por lo que los robots se usaban en las clases como prototipos, sin una expectativa de aplicación a la realidad. Pero como todos sabemos, la situación actual, y el futuro cercano, hacen que la robótica sea un mercado clave para los ingenieros y los informáticos que se forman en las universidades. Como consecuencia, los robots utilizados en las aulas universitarias deben ser actualizados para adecuarlos a la realidad tecnológica que se maneja en el mundo industrial. Este artículo presenta Robobo, un robot móvil educativo de bajo costo desarrollado en la Universidade da Coruña. Robobo combina una base con ruedas simple con un teléfono inteligente, que proporciona la última tecnología al robot. Con Robobo, los estudiantes pueden desarrollar sus propios proyectos usando cámaras, micrófonos o pantallas de alta resolución, acercando la enseñanza universitaria al mercado real que encontrarán cuando finalicen sus estudios.[Abstract] Computer science and engineering majors have been using mobile robots in different subjects for a long time. So far, due primarily to economic constraints, these educational robots have been quite simple in technological terms. This was not a big problem because robotics was not considered a real market in the industry, so robots were used in classes as prototypes, without an expectation of application to reality. But as we all know, the current situation, and the near future, make robotics a key market for engineers and IT graduates in universities. As a consequence, the robots used in the university classrooms must be updated to adapt them to the technological reality that is handled in the industrial world. This article presents Robobo, a low cost educational mobile robot developed at the University of Coruña. Robobo combines a simple wheeled base with a smartphone, which provides the latest technology to the robot. With Robobo, students can develop their own projects using cameras, microphones or highresolution displays, bringing university education closer to the real market they will find when they finish their studies

A perspective on lifelong open-ended learning autonomy for robotics through cognitive architectures

[Abstract]: This paper addresses the problem of achieving lifelong open-ended learning autonomy in robotics, and how different cognitive architectures provide functionalities that support it. To this end, we analyze a set of well-known cognitive architectures in the literature considering the different components they address and how they implement them. Among the main functionalities that are taken as relevant for lifelong open-ended learning autonomy are the fact that architectures must contemplate learning, and the availability of contextual memory systems, motivations or attention. Additionally, we try to establish which of them were actually applied to real robot scenarios. It transpires that in their current form, none of them are completely ready to address this challenge, but some of them do provide some indications on the paths to follow in some of the aspects they contemplate. It can be gleaned that for lifelong open-ended learning autonomy, motivational systems that allow finding domain-dependent goals from general internal drives, contextual long-term memory systems that all allow for associative learning and retrieval of knowledge, and robust learning systems would be the main components required. Nevertheless, other components, such as attention mechanisms or representation management systems, would greatly facilitate operation in complex domains.Ministerio de Ciencia e Innovación; PID2021-126220OB-I00Xunta de Galicia; EDC431C-2021/39Consellería de Cultura, Educación, Formación Profesional e Universidades; ED431G 2019/0

Artificial Intelligence in Pre-University Education: What and How to Teach

This article belongs to the Proceedings of 3rd XoveTIC Conference[Abstract] The present paper is part of the European Erasmus+ project on educational innovation led by the UDC and entitled “AI+: Developing an Artificial Intelligence Curriculum adapted to European High School”. In this paper, the progress achieved during the first year of the project will be presented. Mainly, the definition of the methodological approach for this future subject has been defined, and the AI topics to be dealt with at this age have been established. It has been a great effort to select the most appropriate focus for this subject considering the students’ and teachers’ technical background and the schools’ equipment.European Commission; 2019-1-ES01-KA201-06574

Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework

Abstract: This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.Ministerio de Ciencia, Innovación y Universidades of Spain/FEDER; t RTI2018-101114-B-I00 Erasmus+ Programme of the European Union; 2019-1-ES01-KA201-065742, Centro de Investigación de Galicia “CITIC”; ED431G 2019/01

Motivation as a Tool for Designing Lifelong Learning Robots

[Abstract] Designing robots has usually implied knowing beforehand the tasks to be carried out and in what domains. However, in the case of fully autonomous robots this is not possible. Autonomous robots need to operate in an open-ended manner, that is, deciding on the most interesting goals to achieve in domains that are not known at design time. This obviously poses a challenge from the point of view of designing the robot control structure. In particular, the main question that arises is how to endow the robot with a designer defined purpose and with means to translate that purpose into operational decisions without any knowledge of what situations the robot will find itself in. In this paper, we provide a formalization of motivation from an engineering perspective that allows for the structured design of purposeful robots. This formalization is based on a definition of the concepts of robot needs and drives, which are related through experience to the appropriate goals in specific domains. To illustrate the process, a motivational system to guide the operation of a real robot is constructed using this approach. A series of experiments carried out over it are discussed providing some insights on the design of purposeful motivated operation.This work was partially funded by the EU’s H2020 research programme (grant No 640891 DREAM), Ministerio de Ciencia, Innovación y Universidades of Spain/FEDER (grant RTI2018-101114-B-I00), Xunta de Galicia and FEDER (grant ED431C 2017/12), and by the Spanish Ministry of Education, Culture and Sports through the FPU grant of Alejandro RomeroXunta de Galicia; ED431C 2017/1

AI curriculum for european high schools: an embedded intelligence approach

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUGXunta de Galicia ; ED431G 2019/0

Studying How Innate Motivations Can Drive Skill Acquisition in Cognitive Robots

This article belongs to the Proceedings of XoveTIC ConferenceAbstract: In this paper, we address the problem of how to bootstrap a cognitive architecture to opportunistically start learning skills in domains where multiple skills can be learned at the same time. To this end, taking inspiration from a series of computational models of the use of motivations in infants, we propose an approach that leverages two types of cognitive motivations: exploratory and proficiency based, the latter modulated by the concept of interestingness as an implementation of attentional mechanisms. This approach is tested in an illustrative experiment with a real robot.Xunta de Galicia; ED431C 2017/12Ministerio de Economía y Competitividad; TIN2015-63646-C5-1-