Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos

Documento en PDF a color.

Autores:: Chaves Osorio, José Andrés

Tipo de recurso:: Doctoral thesis

Fecha de publicación:: 2021

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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dc.title.spa.fl_str_mv	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
dc.title.translated.eng.fl_str_mv	Design of a strategy to obtain safe paths from collaborative robot teamwork
title	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
spellingShingle	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos 620 - Ingeniería y operaciones afines Robotics Autonomous robots Robótica Robots autónomos Agent AWMR Collaborative team Cooperation COVID-19 Minefield mobile robotics Path planning Safe routes Search algorithms Strategy for cooperative task Agente AWMR Equipo colaborativo Cooperación COVID-19 Campo minado Robótica móvil Planificación de rutas Rutas seguras Algoritmos de búsqueda Estrategia para tarea cooperativa
title_short	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
title_full	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
title_fullStr	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
title_full_unstemmed	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
title_sort	Diseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativos
dc.creator.fl_str_mv	Chaves Osorio, José Andrés
dc.contributor.advisor.none.fl_str_mv	Gómez Mendoza, Juan Bernardo
dc.contributor.author.none.fl_str_mv	Chaves Osorio, José Andrés
dc.subject.ddc.spa.fl_str_mv	620 - Ingeniería y operaciones afines
topic	620 - Ingeniería y operaciones afines Robotics Autonomous robots Robótica Robots autónomos Agent AWMR Collaborative team Cooperation COVID-19 Minefield mobile robotics Path planning Safe routes Search algorithms Strategy for cooperative task Agente AWMR Equipo colaborativo Cooperación COVID-19 Campo minado Robótica móvil Planificación de rutas Rutas seguras Algoritmos de búsqueda Estrategia para tarea cooperativa
dc.subject.lcsh.none.fl_str_mv	Robotics Autonomous robots
dc.subject.lemb.none.fl_str_mv	Robótica Robots autónomos
dc.subject.proposal.eng.fl_str_mv	Agent AWMR Collaborative team Cooperation COVID-19 Minefield mobile robotics Path planning Safe routes Search algorithms Strategy for cooperative task
dc.subject.proposal.spa.fl_str_mv	Agente AWMR Equipo colaborativo Cooperación COVID-19 Campo minado Robótica móvil Planificación de rutas Rutas seguras Algoritmos de búsqueda Estrategia para tarea cooperativa
description	Documento en PDF a color.
publishDate	2021
dc.date.accessioned.none.fl_str_mv	2021-07-29T15:46:54Z
dc.date.available.none.fl_str_mv	2021-07-29T15:46:54Z
dc.date.issued.none.fl_str_mv	2021
dc.type.spa.fl_str_mv	Trabajo de grado - Doctorado
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/doctoralThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv	http://purl.org/coar/resource_type/c_db06
dc.type.content.spa.fl_str_mv	Text
format	http://purl.org/coar/resource_type/c_db06
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/79865
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/79865 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	eng
language	eng
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spelling	Atribución-NoComercial-SinDerivadas 4.0 InternacionalAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Gómez Mendoza, Juan Bernardo352a44038fe939012b06a03bec791971Chaves Osorio, José Andrés7a56c44f8d9ad1b26b3e52725908f64c2021-07-29T15:46:54Z2021-07-29T15:46:54Z2021https://repositorio.unal.edu.co/handle/unal/79865Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Documento en PDF a color.figuras, tablasThis doctoral thesis was designed and implemented using a strategy of explorer agents and a management and monitoring system to obtain the shortest and safest paths. The strategy was simulated using Matlab R2016 in 10 test environments. The comparisons were made between the results obtained by considering each robot's work and contrasting it with the results obtained by implementing the cooperative-collaborative strategy. For this purpose, were used two path planning algorithms, they are the A* and the Greedy Best First Search (GBFS). Some changes were made to these classic algorithms to improve their performance to guarantee interactions and comparisons between them, transforming them into Incremental Heuristic (IH) algorithms, which gave rise to a couple of agents with new path planners called IH-A* and IH-GBFS. The cooperative strategy was implemented with IH-A* and IH-GBFS algorithms to obtain the shortest paths. The cooperative process was used 300 times in 100 complete tests (3 times in 10 tests in each of 10 environments), which allowed determining that the strategy decreased the original path (without cooperation) in 79% of the cases. In 20.50% of cases, the author identified that the cooperative process, reduced to less than half the original path. The collaborative strategy was implemented to obtain the safer path, using a communications system that allows the interaction among the explorer agents, the test environment, and the management and monitoring system to generate early warnings and compare the risk between paths. In this work, the risk is due to hidden marks found by the explorer agents; for this reason, it is implemented a potential risk function that allows obtaining the path risk estimated. The path risk estimated metric is the one that facilitates the evaluation and comparison of risk between paths to find safer paths. The AWMRs operates using a kinematic model, a controller, a path planner, and sensors that allow them to navigate through the environment gently and safely. Simultaneously with the explorer agents, the administration and monitoring system as a user interface that facilitates the presentation and consolidation of results were implemented. Subsequently, 16 tests were carried out, implementing the complete cooperative-collaborative strategy in four different environments, which had hidden marks. When analyzing the results, it was determined that the Shortest Safest Estimated Path was found in 62.5% of the tests. A WMR and a square test stage were built. In the test scenario, 240 path tracking tests were carried out (the WMR travelled 24 different paths; the WMR travelled each path ten times). The path data were obtained using odometry with encoders onboard the robot and image processing through an external camera. The author apply a tracking error analysis on the WMR path, travelling a circumference of 3.64 m in length. When comparing the path obtained with the WMR kinematic model with the data obtained using image processing, a Mean Absolute Percentage Error (MAPE) of 2,807% was obtained; and with the odometry data, the MAPE was 1,224%. As a general conclusion, this study has numerically identified the relevance of the implementation of the cooperative-collaborative strategy in robotic teamwork to find shortest and safest paths, a strategy applied in test environments that have obstacles and hidden marks. The cooperative-collaborative strategy can be used in different applications that involve displacement in a dangerous place or environment, such as a minefield or a region at risk of spreading COVID-19.Esta tesis doctoral fue diseñada e implementada utilizando una estrategia de agentes exploradores y un sistema de gestión y seguimiento para obtener caminos más cortos y seguros. La estrategia se simuló utilizando Matlab R2016 en 10 entornos de prueba. Las comparaciones se realizaron entre los resultados obtenidos al considerar el trabajo realizado por cada robot y contrastarlo con los resultados obtenidos al implementar la estrategia cooperativa-colaborativa. Para ello, se utilizaron dos algoritmos de planificación de rutas, que son el A* y el Greedy Best First Search (GBFS). Se realizaron algunos cambios a estos algoritmos clásicos para mejorar su rendimiento para garantizar interacciones y comparaciones entre ellos, transformándolos en algoritmos Heurísticos Incrementales (IH), lo que dio lugar a un par de agentes con nuevos planificadores de rutas denominados IH-A * e IH- GBFS. La estrategia cooperativa se implementó con algoritmos IH-A * e IH-GBFS para obtener los caminos más cortos. El proceso cooperativo se utilizó 300 veces en 100 pruebas completas (3 veces en 10 pruebas en cada uno de los 10 entornos), lo que permitió determinar que la estrategia disminuyó la trayectoria original (sin cooperación) en el 79% de los casos. En el 20,50% de los casos, el autor identificó que el proceso cooperativo, redujo la distancia entre inicio y meta a menos de la mitad del recorrido original. La estrategia colaborativa se implementó para obtener el camino más seguro, utilizando un sistema de comunicaciones que permite la interacción entre los agentes exploradores, el entorno de prueba y el sistema de gestión y monitoreo para generar alertas tempranas y comparar el riesgo entre caminos. En este trabajo, el riesgo se debe a las marcas ocultas encontradas por los agentes exploradores; por ello, se implementa una función de riesgo potencial que permite obtener el riesgo de ruta estimado. La métrica estimada de riesgo de ruta es la que facilita la evaluación y comparación de riesgo entre rutas para encontrar rutas más seguras. Los robots autónomos móviles con ruedas (en inglés AWMR) operan utilizando un modelo cinemático, un controlador, un planificador de rutas y sensores que les permiten navegar por el entorno de manera suave y segura. Simultáneamente con los agentes exploradores, el autor implementó un sistema de administración y monitoreo como interfaz de usuario que facilita la presentación y consolidación de resultados. Posteriormente, se realizaron 16 pruebas, implementando la estrategia cooperativa-colaborativa completa en cuatro entornos diferentes, que tenían marcas ocultas. Al analizar los resultados, se determinó que una ruta estimada más corta y más segura se obtenía en el 62.5% de las pruebas. Se construyeron un WMR y un escenario de prueba cuadrado. En el escenario de prueba, se llevaron a cabo 240 pruebas de seguimiento de ruta (el WMR recorrió 24 rutas diferentes; el WMR recorrió cada ruta diez veces). Los datos de la trayectoria se obtuvieron utilizando odometría con encoders a bordo del robot y procesamiento de imágenes a través de una cámara externa. El autor aplica un análisis de error de seguimiento en la ruta recorrida por el WMR, generando una circunferencia de 3,64 m de longitud. Al comparar la ruta obtenida con el modelo cinemático del WMR con los datos obtenidos usando el procesamiento de imágenesse obtuvo un error de porcentaje absoluto medio (MAPE) de 2.807%; y con los datos de odometría, el MAPE fue de 1,224%. Como conclusión general, este estudio ha identificado numéricamente la relevancia de la implementación de la estrategia cooperativa-colaborativa en el trabajo en equipo robótico para encontrar caminos más cortos y seguros, estrategia aplicada en entornos de prueba que poseen obstáculos y marcas ocultas. La estrategia cooperativa-colaborativa puede ser utilizada en diferentes aplicaciones que involucran el desplazamiento en un lugar o entorno peligroso, como pueden ser un campo minado o una región en riesgo de propagación de COVID-19.DoctoradoDoctor en Ingeniería - Ingeniería Automática206 páginasapplication/pdfengUniversidad Nacional de ColombiaManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - AutomáticaDepartamento de Ingeniería Eléctrica y ElectrónicaFacultad de Ingeniería y ArquitecturaManizales, ColombiaUniversidad Nacional de Colombia - Sede Manizales620 - Ingeniería y operaciones afinesRoboticsAutonomous robotsRobóticaRobots autónomosAgentAWMRCollaborative teamCooperationCOVID-19Minefieldmobile roboticsPath planningSafe routesSearch algorithmsStrategy for cooperative taskAgenteAWMREquipo colaborativoCooperaciónCOVID-19Campo minadoRobótica móvilPlanificación de rutasRutas segurasAlgoritmos de búsquedaEstrategia para tarea cooperativaDiseño de una estrategia para la obtención de rutas seguras de trabajo en equipo para robots colaborativosDesign of a strategy to obtain safe paths from collaborative robot teamworkTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Text[1] M. 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Joseph, “Kinematics (joseph stiles beggs),” 1985.Universidad Tecnológica de PereiraLICENSElicense.txtlicense.txttext/plain; charset=utf-83964https://repositorio.unal.edu.co/bitstream/unal/79865/1/license.txtcccfe52f796b7c63423298c2d3365fc6MD51ORIGINAL7914501.2021.pdf7914501.2021.pdfTesis de Doctorado en Ingeniería - Línea de Investigación en Automáticaapplication/pdf29142605https://repositorio.unal.edu.co/bitstream/unal/79865/2/7914501.2021.pdf664e7c9b9229714bb0455bfc97bce290MD52CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.unal.edu.co/bitstream/unal/79865/3/license_rdf4460e5956bc1d1639be9ae6146a50347MD53THUMBNAIL7914501.2021.pdf.jpg7914501.2021.pdf.jpgGenerated Thumbnailimage/jpeg5380https://repositorio.unal.edu.co/bitstream/unal/79865/4/7914501.2021.pdf.jpg61d1c836a57f4f44214bd5a2a4112b54MD54unal/79865oai:repositorio.unal.edu.co:unal/798652023-07-24 23:04:36.856Repositorio Institucional Universidad Nacional de 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