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dc.contributor.advisorSolaque Guzmán, Leonardo Enriquespa
dc.contributor.authorSalgado Luque, Jorge Alejandrospa
dc.contributor.otherSánchez, Guillermospa
dc.contributor.otherRondón Cárdenas, Daniel Santiagospa
dc.coverage.spatialCalle 100spa
dc.date.accessioned2018-10-05T19:46:44Z
dc.date.accessioned2019-12-26T22:10:50Z
dc.date.available2018-10-05T19:46:44Z
dc.date.available2019-12-26T22:10:50Z
dc.date.issued2018-08-16
dc.identifier.urihttp://hdl.handle.net/10654/18049
dc.description.abstractLa pregunta: ¿Dónde me encuentro? Es una de las preguntas más básicas realizadas por la humanidad a lo largo del tiempo. El surgimiento, avance y desarrollo dentro del área de la robótica, tal como es la robótica autónoma, se ha convertido en uno de los logros más exitosos alcanzado al tiempo presente; siendo que un robot por sí mismo pueda realizar tareas y aún comportamientos sin ninguna intervención humana es algo pensado, antiguamente, sólo en la ciencia ficción. La cuestión: ¿Dónde me encuentro? Se ha transformado en: ¿Cómo sabe una unidad robótica dónde se encuentra? Y para responder este interrogante el objetivo de muchas de las investigaciones en este campo de estudio ha sido el de encontrar la mejor técnica o solución que permite al robot darle capacidades de navegación en un modo autónomo. En el contexto de desplazamiento de las plataformas robóticas aéreas en entornos poco estructurados, es decir, donde no se conoce el mapa a priori; es primordial la seguridad de los agentes actuantes dentro del área de trabajo, más aún, cuando se trata de vidas humanas. Para esto, es necesario un robot aéreo capacitado con una buena instrumentación, el cual debe ser capaz de sortear situaciones de riesgo cuando realiza la ejecución de sus labores para llegar a un éxito de misión. El presente trabajo pretende abordar una estrategia de Mapeo y Localización Simultánea dentro del sistema operativo robótico ROS, de manera que una plataforma robótica terrestre (Pioneer3DX) o aérea (DJI Matrice 600 Pro) pueda desplazarse en un espacio tridimensional con capacidad de auto-localizarse y tomar decisiones en tiempo real para no colisionar con obstáculos al dirigirse a un punto de misión definido. Se logra ejecutar el algoritmo de SLAM del paquete slam_gmapping con interfaz ROS y visualización en RVIZ con la plataforma robótica terrestre y aérea; con la capacidad de evadir obstáculos estáticos y dinámicos.spa
dc.description.tableofcontents1. Introducción 1.1 Planteamiento del Problema 1.2 Objetivos 1.2.1 Objetivo General 1.2.2 Objetivos Específicos 1.3 Justificación 1.4 Metodología 2 Marco Teórico 2.1 Mapeo y Localización Simultánea (SLAM) 2.1.1 Características de SLAM 2.1.2 Formulación y estructura del problema de SLAM 2.2 Modelo Cinemático - Plataforma Robótica Móvil Terrestre 2.3 Modelo Cinemático - Plataforma Robótica Móvil Aérea 2.4 Filtro de Kalman 2.4.1 Proceso de Estimación 2.4.2 Introducción de orígenes computacionales del Filtro de Kalman 2.4.3 Algoritmo del Filtro Discreto de Kalman 2.5 Filtro de Kalman Extendido (EKF) 2.5.1 Orígenes Computacionales del Filtro de Kalman Extendido 2.6 Filtro de Partículas Rao-Blackwellized 3 Software 3.1 Robotic Operating System (ROS) 3.2 ROS Enhancement Proposals (REPs) 3.2.1 REP-103 3.2.2 REP-105 3.3 Paquetes de ROS Utilizados 3.3.1 SLAM con Gmapping (slam_gmapping) 3.3.2 Move Base 3.3.3 Robot Localization 3.3.4 DJI SDK 3.3.5 ZED ROS Wrapper 3.3.6 URG Node 3.3.7 Advanced Navigation Driver 3.3.8 RosAria 4 Hardware 4.1 Cámara Estereoscópica - ZED 4.2 Sensor Láser – Hokuyo 4.3 Spatial Advanced Navigation 4.4 Plataforma Robótica Móvil Terrestre – Pioneer3DX 4.5 Plataforma Robótica Móvil Aérea - DJI Matrice 600 Pro 4.6 Sistema de Procesamiento – AlienWare Alpha 4.7 Sistema de Procesamiento – Dell Portátil 5 Simulaciones 6 Resultados Experimentales 6.1 Plataforma Terrestre 6.2 Plataforma Aérea 7 Conclusiones y Trabajos Futuros 8 Anexosspa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rightsDerechos Reservados - Universidad Militar Nueva Granada, 2018spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.5/co/spa
dc.titleDesplazamiento seguro y autónomo en entornos poco estructurados basado en técnicas de SLAM para un vehículo aéreo no tripuladospa
dc.typeinfo:eu-repo/semantics/bachelorThesisspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.subject.lembAVIONES SIN PILOTOspa
dc.subject.lembROBOTICAspa
dc.publisher.departmentFacultad de Ingenieríadspa
dc.type.localTrabajo de gradospa
dc.description.abstractenglishThe question: Where am I? It is one of the most basic questions asked by humanity over time. The emergence, advancement and development within the area of robotics, such as autonomous robotics, has become one of the most successful achievements reached at the time; Being that a robot by itself can perform tasks and even behaviors without any human intervention is something thought, formerly, only in science fiction. The question: Where am I? It has been transformed into: How does a robotic unit know where it is? And to answer this question the objective of many of the investigations in this field of study has been to find the best technique or solution that allows the robot to give navigation capabilities in an autonomous mode. In the context of the displacement of aerial robotic platforms in unstructured environments, that is, where the a priori map is not known; the safety of the agents acting within the workspace area is paramount, especially when it comes to human lives. For this, a trained aerial robot with a good instrumentation is necessary, which must be able to overcome situations of risk when it carries out its tasks to reach a mission success. This paper aims to address a strategy of simultaneous location and mapping within the robotic operating system ROS, so that a terrestrial robot platform (Pioneer3DX) or aerial (DJI Matrice 600 Pro) can move in a three-dimensional space with the ability to auto-locate and make decisions in real time so that do not collide with obstacles when going to a defined mission target. It is possible to execute the SLAM algorithm of the slam_gmapping package with ROS interface and visualization in RVIZ with the terrestrial and aerial robotic platform; with the ability to evade static and dynamic obstacles.eng
dc.title.translatedSafe and autonomous displacement in unstructured environments based on SLAM Techniques for an unmanned aerial vehiclespa
dc.subject.keywordsSLAMspa
dc.subject.keywordsNavigationspa
dc.subject.keywordsPioneer3DXspa
dc.subject.keywordsDJI Matrice 600 Prospa
dc.subject.keywordsROSspa
dc.subject.keywordsGmappingspa
dc.subject.keywordsLaser Sensorspa
dc.subject.keywordsSpatial Advanced Navigationspa
dc.subject.keywordsZEDspa
dc.subject.keywordsmove_basespa
dc.subject.keywordsrobot_localizationspa
dc.subject.keywordsslam_gmappingspa
dc.subject.keywordsHokuyospa
dc.publisher.programIngeniería en Mecatrónicaspa
dc.creator.degreenameIngeniero en Mecatrónicaspa
dc.description.degreelevelPregradospa
dc.publisher.facultyIngeniería - Ingeniería en Mecatrónicaspa
dc.type.dcmi-type-vocabularyTextspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadasspa
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dc.subject.proposalSLAMspa
dc.subject.proposalNavegaciónspa
dc.subject.proposalPioneer3DXspa
dc.subject.proposalDJI Matrice 600 Prospa
dc.subject.proposalROSspa
dc.subject.proposalGmappingspa
dc.subject.proposalSensor Láserspa
dc.subject.proposalSpatial Advanced Navigationspa
dc.subject.proposalZEDspa
dc.subject.proposalmove_basespa
dc.subject.proposalrobot_localizationspa
dc.subject.proposalslam_gmappingspa
dc.subject.proposalHokuyospa
dc.publisher.grantorUniversidad Militar Nueva Granadaspa


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