Planificación de trayectorias óptimas de robots móviles empleando el mapeo de celdas

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dc.contributor.advisorOsorio Londoño, Gustavo Adolfo
dc.contributor.authorGrisales Ramírez, Efraín
dc.contributor.orcidGrisales Ramírez, Efraín [0009000814296566]spa
dc.contributor.researchgroupPercepción y Control Inteligente (Pci)spa
dc.date.accessioned2023-10-03T02:17:55Z
dc.date.available2023-10-03T02:17:55Z
dc.date.issued2023
dc.descriptiongraficas, tablasspa
dc.description.abstractEl problema de planificación de trayectorias es de importancia dentro de la robótica móvil, puesto que es indispensable generar caminos de referencia que eviten obstáculos y de fácil seguimiento por los sistemas autónomos. La solución dada por los algoritmos de planificación puede ser de diferente naturaleza, aumentando o disminuyendo la complejidad computacional. En este documento se propone un método para la planificación de trayectorias de robots móviles empleando el algoritmo de mapeo de celdas (AMC), el cual contiene las restricciones cinemáticas y dinámicas del robot, así como las del entorno, permitiendo generar trayectos de fácil seguimiento por el sistema. También contiene la información necesaria con el fin de dar solución al problema de optimización multiobjetivo. El algoritmo consiste en dividir el espacio de estados en celdas y luego simular la evolución del sistema dinámico del móvil para cada condición inicial; con esto se generan grafos que contienen la información de las conexiones entre celdas en términos de distancia, tiempo, esfuerzo de control y energía. Con esta información se solucionan los problemas de optimización simple o multiobjetivo, según sea la función de costo empleada para encontrar el camino más corto entre dos puntos con el algoritmo de Dijkstra. Además, en este documento se introducen algunos conceptos de control óptimo que serán empleados en la planificación de trayectorias de robots móviles. Estos conceptos se aplican inicialmente al doble integrador (DI) en tiempo continuo, debido a que éste emula el comportamiento de un robot sin masa. Posteriormente se implementa el AMC para solucionar los mismos problemas de optimización en forma discreta para el movimiento en 1 y 2 dimensiones, y se extiende el concepto a la aplicación en robots móviles de guiado diferencial, así como para el Robotino de FESTO. (Texto tomado de la fuente)spa
dc.description.abstractThe trajectory planning problem is of importance in mobile robotics since it is essential to generate reference paths that avoid obstacles and are easy to follow for autonomous systems. The solutions provided by planning algorithms can vary in nature, either increasing or decreasing computational complexity. This paper presents a method for planning mobile robot trajectories using the Cell Mapping Algorithm (CMA), which incorporates the kinematic and dynamic constraints of the robot as well as those of the environment. This approach enables the generation of trajectories that are easy for the system to follow and includes the necessary information to address multi-objective optimization problems. The algorithm involves dividing the state space into cells and then simulating the evolution of the mobile robot's dynamic system for each initial condition. This process generates graphs that contain information about the connections between cells in terms of distance, time, control effort, and energy. With this information, simple or multi-objective optimization problems can be solved, depending on the cost function used to find the shortest path between two points, typically implemented with Dijkstra's algorithm. Also, this thesis introduces some optimal control concepts that will be used in path planning of mobile robots. These concepts are initially applied to continuous-time double integrator (DI), because it emulates behavior of a massless robot. Subsequently, the AMC is implemented to solve same optimization problems in discrete form for motion in 1 and 2 dimensions, and concept is extended to the application in differential guided mobile robots, as well as for FESTO Robotino.eng
dc.description.curricularareaEléctrica, Electrónica, Automatización Y Telecomunicaciones.Sede Manizalesspa
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingenieríaspa
dc.description.researchareaSistemas de Control y Robóticaspa
dc.format.extentxxiv, 136 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/84744
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Manizalesspa
dc.publisher.facultyFacultad de Ingeniería y Arquitecturaspa
dc.publisher.placeManizales, Colombiaspa
dc.publisher.programManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Automáticaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc620 - Ingeniería y operaciones afinesspa
dc.subject.proposalAlgoritmo de Dijsktraspa
dc.subject.proposalAlgoritmo de mapeo de celdasspa
dc.subject.proposalDoble integradorspa
dc.subject.proposalModelo dinámicospa
dc.subject.proposalOptimización combinatoriaspa
dc.subject.proposalOptimización continuaspa
dc.subject.proposalOptimización discretaspa
dc.subject.proposalRobot móvil de guiado diferencialspa
dc.subject.proposalTeoría de control óptimospa
dc.subject.proposalDijsktra algorithmeng
dc.subject.proposalCell mapping algorithmeng
dc.subject.proposalDiscrete optimizationeng
dc.subject.proposalDouble integratoreng
dc.subject.proposalDynamic modeleng
dc.subject.proposalCombinatorial optimizationeng
dc.subject.proposalContinuous optimizationeng
dc.subject.proposalDifferential guided mobile roboteng
dc.subject.proposalOptimal control theoryeng
dc.titlePlanificación de trayectorias óptimas de robots móviles empleando el mapeo de celdasspa
dc.title.translatedOptimal trajectory planning for mobile robots using cell mappingeng
dc.typeTrabajo de grado - Doctoradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_db06spa
dc.type.coarversionhttp://purl.org/coar/version/c_71e4c1898caa6e32spa
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dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/doctoralThesisspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentBibliotecariosspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentPúblico generalspa
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