Educational framework using robots with vision for constructivist teaching of robotics to pre-university students

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Title: Educational framework using robots with vision for constructivist teaching of robotics to pre-university students
Other Titles: Entorno educativo usando robots con visión para la enseñanza constructivista de Robótica a estudiantes preuniversitarios
Authors: Vega Pérez, Julio
Research Director: Cañas Plaza, José María | Cazorla, Miguel
Center, Department or Service: Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: Teaching Robotics | Vision | AI | Python | Raspberry Pi | PiCamera | PiBot | STEM education
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Date Created: 2018
Issue Date: 2018
Date of defense: 21-Sep-2018
Publisher: Universidad de Alicante
Abstract: Robotics will be a dominant area in society throughout future generations. Nowadays its presence is increasing in the majority of contexts of daily life, with devices and mechanisms which facilitate the accomplishment of diverse daily tasks; as well as at labor level, where machines occupy more and more jobs. This increase in the presence of autonomous robotic systems in society is due to the great efficiency and security they offer compared to human capacity, thanks mainly to the enormous precision of their sensor and actuator systems. Among these, vision sensors are of utmost importance. Humans and many animals enjoy powerful perception systems in a natural way, but which in Robotics constitutes a constant line of research. The main problem lies in the correct interpretation of visual data and the extraction of relevant information from camera images. Thus, Robotics becomes something beyond an scientific are, but also a social and cultural topic. Therefore, it is essential to raise an early awareness and train younger students to acquire the skills which will be most demanded in the short and mid-term future. In doing so, we will be ensuring their integration into a labor market dominated by intelligent robotic systems. In addition to having a high capacity for reasoning and decision-making, these robots incorporate important advances in their perceptual systems, allowing them to interact effectively in the working environments of this new industrial revolution. Since a few years ago, there are different Educational Robotics kits available in the market which are designed to be used in pre-university education. To use them as a learning tool, a correct teacher training is necessary, as well as a change in the teaching-learning methodology and in the educational environment in general. In addition, taking into account that young people live immersed in a constant environment of technological learning, most of these kits usually have a short period of interest for students, who demand motivating intellectual challenges. This thesis aims to provide several solutions to some classic problems inherent to Robotics, such as navigation and localization, but using a camera as the main sensor. In addition, a learning framework for teaching of Robotics with Vision as a subject is presented. Using it the students at pre-university curricular level learn the principles of Science and Engineering and the computer programming skills demanded in today's society. The use of Python language and its exercises about robots with vision makes this learning framework unique and more powerful than other existing frameworks. This teaching framework has been successfully used in several secondary education schools during the last two academic years (2016/2017 and 2017/2018), which includes: its software infrastructure, its hardware platform, an academic curriculum with theoretical and practical content, as well as a constructivist pedagogical methodology. The performance and satisfaction of more than 2,000 students and teachers using it, in curricular subjects such as Programming, Robotics and Technology and ICTs of Secondary Education (CSO) and extracurricular activities, have been evaluated.
Language: eng
Type: info:eu-repo/semantics/doctoralThesis
Rights: Licencia Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0
Appears in Collections: Doctoral theses

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