Tesis Tecnologías de la Información

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Aplicación del algoritmo de aprendizaje por refuerzo Q-Learning para la generación de trayectorias óptimas en plataformas robóticas
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Tecnologías de la Información, 2024-09) Moya Quinatoa, Kevin Alejandro; Álvarez Mayorga, Edison Homero
Technological innovation is fundamental for business development and efficiency in Industry 4.0, which demands staying updated with the latest technologies. The rapid growth in the use of artificial intelligence (AI) offers high benefits and low operational costs, creating more stable and automated work environments. However, one of the greatest challenges in applying AI is the complexity of trajectory planning for mobile robots, as their behavior varies according to the scenario and algorithms used, making it difficult to compare learning and performance between different methods. This research, as part of the project titled "Use of Deep Learning Techniques for Trajectory Planning of Mobile Robots within an Industrial Process," developed a trajectory planning algorithm using Q-learning and a multi-agent system that collaborate in decision-making. This algorithm employs odometry and laser sensor signals to manage states and rewards. Tests were conducted in a ROS simulation environment and replicated in a real-world scenario with the KUKA Youbot robot to implement the algorithm's actions. The simulated environment recreates a space with obstacles, where a master agent evaluates the decisions made by the odometry agent and the laser sensor agent to autonomously make a final decision. This contributes to the comparison of AI algorithms in terms of efficiency and effectiveness within the mentioned project, laying a foundation for future improvements in trajectory planning on mobile platforms.
Aplicación del algoritmo de aprendizaje por refuerzo state-action-reward-state-action (SARSA) para la generación de trayectorias óptimas en plataformas robóticas
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Tecnologías de la Información, 2024-08) Sarzosa Villarroel, José Jeanpierre; Álvarez Mayorga, Edison Homero
Path planning for mobile robots is crucial to improve efficiency and reduce operational risks in the 4.0 industry. Companies are looking to implement advanced technologies such as artificial intelligence and reinforcement learning to automate industrial processes. This study was developed using the Kanban methodology, allowing the work to be broken down into several stages and tasks for monitoring and control. The implementation of the reinforcement learning algorithm SARSA to generate optimal trajectories in mobile robotic platforms is addressed, focusing on adapting and applying this "on-policy" algorithm, which updates its action values based on the direct experience with the environment. The experimental process included implementing the SARSA algorithm in a simulated environment for the autonomous-capable KUKA YouBot robot and a LIDAR sensor on an Nvidia Jetson AGX Orin module. The agent interacted with the environment through training episodes, learning through ε-greedy policy exploration and exploitation of the current and next actions available and computed based on the current and next states, respectively. The trained models were tested in a real environment with the KUKA YouBot robot to validate their performance under practical conditions. Finally, the results were integrated with a larger project using Deep Learning techniques to optimize autonomous trajectories in mobile robots within industrial processes, demonstrating the feasibility and advantages of using reinforcement learning algorithms in advanced robotic applications.
Aplicación móvil para la gestión y notificación de alertas de seguridad alimentaria y crecimiento en niños con desnutrición en la “Fundación Casa De Fe” de Shell
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Tecnologías de la Información, 2023-09) Cordova Cuesta, Bryan Dennis; Álvarez Mayorga, Edison Homero
Mobile applications have established themselves as valuable tools in various areas. including health, due to their ability to provide relevant information, improve the efficiency of healthcare processes. as well as facilitate interaction and communication between healthcare professionals and patients. This project aims to implement an application for the management and notification of food security alerts of children residing in the "Casa de Fe Foundation" of the Shell canton of the province of Pastaza. This alert and management system will contribute to real-time monitoring of nutrition. children's growth and facilitating communication and interaction between health professionals and patients. The mobile application was developed using the Flutter framework designed by Google, which uses the Dart programming language and with the Visual Studio Code code editor as an Integrated Development Environment (IDE). The management of the Backend is done through Firebase services, which are Cloud Firestore. Storage. Messaging. Authentication. Test Lab, and Functions. In the design system. Material Design 3 was implemented to obtain a modern, aesthetic, and standardized design, all this together with the application of the Mobile-D development methodology, for the great flexibility, adaptability, and speed to changes for the development of the application.
Plataforma virtual desarrollada con el Framework Spring para la planificación y organización de teletrabajo en el GAD Municipalidad de Ambato.
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Tecnologías de la Información, 2023-09) Morocho Valle, Andrés Patricio; Álvarez Mayorga, Edison Homero
Technological advances have significantly improved the services provided by both public and private institutions. Using analysis and various resources, these institutions seek to enhance the effectiveness of their activities. The planning proposed by each departmental director requires each employer to adopt a strategy to successfully accomplish these activities without having a clear path to the goal, resulting in time loss while analyzing each task to be performed. Each department plays a crucial role in meeting the specific needs of their respective areas, which necessitates the incorporation of objectives and planning to optimize time management and avoid delays in task completion. The presented proposal addresses a research problem and demonstrates an interest in implementing a system that enhances the quality of work delivery at the GAD Municipalidad de Ambato. This system aims to improve efficiency and effectiveness in work activities, thereby providing better service in the workplace. Additionally. processes and strategies will be established to evaluate the effectiveness and fulfillment of tasks, allowing the employer to measure success or potential delays in the proposed activities. The main objective is to improve worker performance and achieve greater departmental effectiveness at the GAD Municipalidad de Ambato.