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Diseño de un sistema que determine regiones de agarre de objetos cilíndricos en un entorno semi-estructurado basado en visión
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional |
dc.contributor.advisor | Cárdenas Herrera, Pedro Fabián |
dc.contributor.advisor | Grisales Palacio, Victor Hugo |
dc.contributor.author | Ochoa Morón, Daniel Francisco |
dc.date.accessioned | 2024-07-18T14:28:59Z |
dc.date.available | 2024-07-18T14:28:59Z |
dc.date.issued | 2024-01-31 |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/86555 |
dc.description | ilustraciones, diagramas, fotografías |
dc.description.abstract | La presente tesis de maestría se focaliza en el desarrollo de un sistema destinado a determinar las regiones de agarre de objetos cilíndricos, específicamente botellas plásticas, en un entorno semi-estructurado utilizando visión por computadora. A pesar de la diversidad de formas, tamaños y colores que presentan las botellas, se asume un tamaño promedio de 500 ml para la investigación. El proyecto tiene como objetivo abordar desafíos en la manipulación robótica y la automatización, especialmente en aplicaciones industriales. Se inicia con la creación de un banco de imágenes que sirve como base para un sistema de procesamiento de imágenes, el cual, junto con herramientas de inteligencia artificial, permite entrenar una red neuronal específica para la tarea de agarre. La presente investigación profundiza en los métodos y tecnologías utilizados en la planificación de agarre y la manipulación robótica, destacando el uso de técnicas de aprendizaje profundo. El documento se encuentra organizado en capítulos que abarcan el contexto de la investigación, la motivación, el trabajo relacionado, los objetivos específicos y el desarrollo del sistema para la generación automática de regiones de agarre basadas en visión por computadora y aprendizaje automático. En el marco del desarrollo de la presente investigación, se centró en el análisis físico de un número determinado de objetos dispuestos en escena y las características físicas y funcionales de un gripper de dos dedos empleado para ejecutar una tarea de agarre específica. A partir de un sistema de percepción visual bidimensional ajustado y la extracción de características geométricas de los objetos, se diseñó e implementó un sistema algorítmico capaz de establecer regiones de agarre a lo largo de los objetos empleados. Posteriormente, se estableció un número de parámetros de evaluación heurísticos con el objetivo de determinar la viabilidad de cada una de las regiones encontradas sobre cada objeto en relación con su espacio circundante. (Texto tomado de la fuente). |
dc.description.abstract | This master's thesis focuses on the development of a system aimed at determining the grasping regions of cylindrical objects, specifically plastic bottles, in a semi-structured environment using computer vision. Despite the diversity of shapes, sizes, and colors that bottles present, an average size of 500 ml is assumed for the research. The project aims to address challenges in robotic manipulation and automation, especially in industrial applications. It begins with the creation of an image bank that serves as the basis for an image processing system, which, along with artificial intelligence tools, allows the training of a specific neural network for the grasping task. This research delves into the methods and technologies used in grasp planning and robotic manipulation, highlighting the use of deep learning techniques. The document is organized into chapters that cover the context of the research, the motivation, related work, specific objectives, and the development of the system for the automatic generation of grasping regions based on computer vision and machine learning. In the framework of the development of this research, the focus was on the physical analysis of a determined number of objects arranged in the scene and the physical and functional characteristics of a two-finger gripper used to perform a specific grasping task. Based on an adjusted two-dimensional visual perception system and the extraction of geometric characteristics of the objects, an algorithmic system was designed and implemented to establish grasping regions along the employed objects. Subsequently, a number of heuristic evaluation parameters were established to determine the feasibility of each of the regions found on each object in relation to its surrounding space. |
dc.format.extent | viii, 89 páginas |
dc.format.mimetype | application/pdf |
dc.language.iso | spa |
dc.publisher | Universidad Nacional de Colombia |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject.ddc | 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería |
dc.title | Diseño de un sistema que determine regiones de agarre de objetos cilíndricos en un entorno semi-estructurado basado en visión |
dc.type | Trabajo de grado - Maestría |
dc.type.driver | info:eu-repo/semantics/masterThesis |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
dc.publisher.program | Bogotá - Ingeniería - Maestría en Ingeniería - Automatización Industrial |
dc.description.degreelevel | Maestría |
dc.description.degreename | Magíster en Ingeniería - Automatización Industrial |
dc.description.researcharea | Robótica industrial y grasping |
dc.identifier.instname | Universidad Nacional de Colombia |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl | https://repositorio.unal.edu.co/ |
dc.publisher.faculty | Facultad de Ingeniería |
dc.publisher.place | Bogotá, Colombia |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá |
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dc.rights.accessrights | info:eu-repo/semantics/openAccess |
dc.subject.proposal | Agarre |
dc.subject.proposal | Aprendizaje profundo |
dc.subject.proposal | Manipulador |
dc.subject.proposal | Visión de máquina |
dc.subject.proposal | Grasping |
dc.subject.proposal | Deep learning |
dc.subject.proposal | Manipulator |
dc.subject.proposal | Machine vision |
dc.subject.unesco | Inteligencia artificial |
dc.subject.unesco | Artificial intelligence |
dc.subject.unesco | Propiedad física |
dc.subject.unesco | Physical properties |
dc.title.translated | Design of a system that determines grasping regions of cylindrical objects in a semi-structured vision-based environment |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa |
dc.type.content | Text |
dc.type.redcol | http://purl.org/redcol/resource_type/TM |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |
dcterms.audience.professionaldevelopment | Estudiantes |
dcterms.audience.professionaldevelopment | Investigadores |
dc.contributor.orcid | Ochoa Morón, Daniel [0000-0003-1042-4379] |
dc.contributor.cvlac | Ochoa Morón, Daniel [1eHzLpAAAAAJ] |
dc.subject.wikidata | visión artificial |
dc.subject.wikidata | computer vision |
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