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tfg y tfm en publicaciones
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‎_data/other.yml‎

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- title: "Development of a system for the validation of industrial parts pose on conveyor belts with a focus on simulation and advanced experimentation (Master's Thesis)"
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date: 15 feb. 2024
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url: https://digibuo.uniovi.es/dspace/handle/10651/76231
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language: Spanish
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image: '/assets/publications_images/other/tfm.png'
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description: |
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This project focuses on developing a system that uses reference and current images from a 2D camera to monitor and analyze parts on a conveyor belt in an industrial environment. Graphical user interfaces, communication interfaces, and software are implemented for integrating sensor data, running preprocessing algorithms, motion detection, feature extraction and comparison, as well as object recognition using classical computer vision techniques. A practical solution is proposed, developed under the Qt framework, supported by a robust simulator that facilitates the experimentation and refinement of algorithms in simulated 3D industrial environments. The simulator is presented as a versatile tool that can support the research of various computer vision and machine learning techniques; developed using the OpenGL standard and the C++ programming language with an object-oriented approach, it serves as a powerful and versatile tool for 3D emulation of industrial spaces. The implemented algorithm, using the OpenCV library, acts as an analytical classifier to determine the validity of a part's pose on a production line. Two data sources are used: a static collection of images (reference parts) and pre-calculated feature vectors, and on the other hand, frames from a 2D camera (parts to be validated). The system employs quasi-intelligent algorithmic entities to process images and other signals, perform numerical analysis, feature recognition, and other tasks, generating a final response based on quantitative estimates, votes, weightings, and empirical thresholds. The combination of multiple algorithms proves effective in handling variations and complex deformations. An experimental phase is highlighted, both in simulation and reality, where various environments and conditions are set up to measure the system’s ability to classify valid and invalid parts, as well as its accuracy in adverse scenarios. Finally, after testing the system using statistical repeatability analysis to evaluate its robustness under various cases, the results are analyzed, and it is concluded that the system as a whole, along with the implemented algorithms, proves effective, culminating in a comprehensive solution that successfully addresses the challenge of monitoring and analyzing the pose of parts on a production line.
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- title: "Introductory, Descriptive, and Practical Essay on Neural Networks"
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date: 05 jun. 2023
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url: '/assets/publications_pdfs/other/Ensayo_CNNs.pdf'
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description: |
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This document encompasses several words addressing matters related to the art of creating the quality of discernment, namely, Artificial Intelligence. More specifically, it focuses on one of the most significant foreign contributions to this field: artificial neural networks (ANNs), which are currently highly popular due to their most important functional characteristic—the ability to learn automatically. This capability does not aim to formally create knowledge but rather emulate it through training or learning. Juxtaposed with the results attached to this document, which provide various experiments using MATLAB tools—particularly studying convolutional (artificial) neural networks—it is intended for the reader to accurately grasp and absorb numerous concepts related to these topics and many others that constitute, as a broad ensemble, artificial intelligent systems. All of this is undertaken while keeping in mind the question that, at the time, brilliantly ignited the beginning of this field of study: Can machines think beyond what we can instruct them? A question “whose ramifications continue to be explored to this day.”
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Based on final master's course assignment report.
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- title: "Integration of an educational omnidirectional autonomous mobile robot in ROS (Bachelor's Thesis)"
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date: 19 jul. 2022
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url: https://digibuo.uniovi.es/dspace/handle/10651/76274
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language: Spanish
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image: '/assets/publications_images/other/tfg.png'
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description: |
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This document is part of a larger work within the context of an analytical and descriptive approach to mobile robotics and the open-source software framework ROS. It takes advantage of the availability of an educational, omnidirectional commercial mobile robot to integrate it, from scratch, into this metasystem, using the URDF markup language format, creating and developing various plugins, packages, and nodes to carry out the simulation and real implementation of the robot’s hardware components. Among other things, it includes the study, under this specific framework, of embedded devices such as SBCs (Raspberry Pi) or Arduino controllers. Initially, this work introduces several highly relevant concepts in a notably qualitative manner, belonging to specific fields of study that are fundamental to understanding the overall scope of the project. Given that much of the work is centered around the ROS environment, it also intensively explores various other aspects related to the mobile robot to expand the range of possibilities that can be abstracted based on this proposed work. Later, the process followed to successfully integrate the robot model into the ROS platform (using Gazebo as the simulation environment) is analyzed, along with successfully controlling the movement of its motors or actuators, intercommunicating the microcomputer and microcontroller boards of the robotic system, and incorporating the necessary sensor and node structure to achieve a mobile robot that autonomously performs basic navigation and mapping tasks (both in simulation and in reality), among others. Finally, several short- and long-term proposals are briefly presented and discussed, which could serve as extensions, expansions, or future opportunities for this project.
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- title: Processor vs Controller
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date: 01 sep. 2021
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url: '/assets/publications_pdfs/other/Procesador_vs_Controlador.pdf'

‎_data/publications.yml‎

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- title: "Development of a system for the validation of industrial parts pose on conveyor belts with a focus on simulation and advanced experimentation (Master's Thesis)"
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date: 15 feb. 2024
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url: https://digibuo.uniovi.es/dspace/handle/10651/76231
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language: Spanish
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image: '/assets/publications_images/other/tfm.png'
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description: |
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This project focuses on developing a system that uses reference and current images from a 2D camera to monitor and analyze parts on a conveyor belt in an industrial environment. Graphical user interfaces, communication interfaces, and software are implemented for integrating sensor data, running preprocessing algorithms, motion detection, feature extraction and comparison, as well as object recognition using classical computer vision techniques. A practical solution is proposed, developed under the Qt framework, supported by a robust simulator that facilitates the experimentation and refinement of algorithms in simulated 3D industrial environments. The simulator is presented as a versatile tool that can support the research of various computer vision and machine learning techniques; developed using the OpenGL standard and the C++ programming language with an object-oriented approach, it serves as a powerful and versatile tool for 3D emulation of industrial spaces. The implemented algorithm, using the OpenCV library, acts as an analytical classifier to determine the validity of a part's pose on a production line. Two data sources are used: a static collection of images (reference parts) and pre-calculated feature vectors, and on the other hand, frames from a 2D camera (parts to be validated). The system employs quasi-intelligent algorithmic entities to process images and other signals, perform numerical analysis, feature recognition, and other tasks, generating a final response based on quantitative estimates, votes, weightings, and empirical thresholds. The combination of multiple algorithms proves effective in handling variations and complex deformations. An experimental phase is highlighted, both in simulation and reality, where various environments and conditions are set up to measure the system’s ability to classify valid and invalid parts, as well as its accuracy in adverse scenarios. Finally, after testing the system using statistical repeatability analysis to evaluate its robustness under various cases, the results are analyzed, and it is concluded that the system as a whole, along with the implemented algorithms, proves effective, culminating in a comprehensive solution that successfully addresses the challenge of monitoring and analyzing the pose of parts on a production line.
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- title: "Integration of an educational omnidirectional autonomous mobile robot in ROS (Bachelor's Thesis)"
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date: 19 jul. 2022
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url: https://digibuo.uniovi.es/dspace/handle/10651/76274
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language: Spanish
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image: '/assets/publications_images/other/tfg.png'
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description: |
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This document is part of a larger work within the context of an analytical and descriptive approach to mobile robotics and the open-source software framework ROS. It takes advantage of the availability of an educational, omnidirectional commercial mobile robot to integrate it, from scratch, into this metasystem, using the URDF markup language format, creating and developing various plugins, packages, and nodes to carry out the simulation and real implementation of the robot’s hardware components. Among other things, it includes the study, under this specific framework, of embedded devices such as SBCs (Raspberry Pi) or Arduino controllers. Initially, this work introduces several highly relevant concepts in a notably qualitative manner, belonging to specific fields of study that are fundamental to understanding the overall scope of the project. Given that much of the work is centered around the ROS environment, it also intensively explores various other aspects related to the mobile robot to expand the range of possibilities that can be abstracted based on this proposed work. Later, the process followed to successfully integrate the robot model into the ROS platform (using Gazebo as the simulation environment) is analyzed, along with successfully controlling the movement of its motors or actuators, intercommunicating the microcomputer and microcontroller boards of the robotic system, and incorporating the necessary sensor and node structure to achieve a mobile robot that autonomously performs basic navigation and mapping tasks (both in simulation and in reality), among others. Finally, several short- and long-term proposals are briefly presented and discussed, which could serve as extensions, expansions, or future opportunities for this project.

‎_includes/about/publications.html‎

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<div class="col mt-4">
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<div class="timeline-body bg-themed">
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{% for item in site.data.publications %}
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<div class="timeline-item">
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<div class="content">
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<h2>{{ item.title }}</h2>
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<h6 class="date">{{ item.date }}</h6>
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<div style="display: flex; align-items: center; gap: 10px;">
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<h6 class="url"><a target="_blank" href="{{ item.url }}">Link to PDF</a></h6>
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<h6 class="language">- {{ item.language }}</h6>
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</div>
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<strong>Description:</strong>
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<p style="text-align:justify; font-size:13px"><i>{{ item.description }}</i></p>
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<img src="{{ item.image }}" alt="" class="center">
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</div>
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</div>
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{% endfor %}
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</div>
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</div>

‎pages/publications.md‎

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# **Publications**
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<div class="row">
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{% include about/publications.html %}
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</div>
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## **Preprints**
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Eventually, I research a few exciting topics in image processing and computer vision.

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