Método para el desarrollo de aplicaciones en robótica de servicios basados en industria 4.0 y computación en la nube.

dc.contributor.advisorJiménez Builes, Jovani Alberto
dc.contributor.advisorAcosta Amaya, Gustavo Alonso
dc.contributor.authorSerrate Hincapie, Alejandro
dc.contributor.researchgroupGIDIA: Grupo de Investigación y Desarrollo en Inteligencia Artificialspa
dc.date.accessioned2021-10-08T21:27:39Z
dc.date.available2021-10-08T21:27:39Z
dc.date.issued2021-10-06
dc.descriptiondocumento en formato PDF que describe el desarrollo de la tesis de maestría la cual tiene por nombre: Método para el desarrollo de aplicaciones en robótica de servicios basados en industria 4.0 y computación en la nubespa
dc.descriptionIlustracionesspa
dc.description.abstractEn el presente trabajo se llevó a cabo el desarrollo de una metodología para el desarrollo de aplicaciones en robótica de servicios basado en industria 4.0 y computación en la nube. La primera parte del trabajo consiste en caracterizar los elementos de industria 4.0 aplicables a la robótica de servicios para interiores. Una vez definidos, se identificaron los modelos de computación en la nube aplicables a la robótica de servicios, y luego se incorporaron técnicas en inteligencia artificial para el control de la navegación de robots móviles en entornos interiores. Después se integraron los elementos de la industria 4.0 y computación en la nube, para la navegación autónoma de un sistema robótico. Con lo anterior se construyó una metodología, adicionándole elementos como sensorica, locomoción, manipulación, desarrollo web, fuentes de datos, entornos de desarrollo en la nube, simulación, arquitecturas de control, y marcadores fiduciales visuales. Finalmente se validó el método propuesto a través de la realización de un conjunto de pruebas en un escenario logístico, generando con ello resultados y conclusiones. (Texto tomado de la fuente)spa
dc.description.abstractIn the present work, the development of a methodology for the development of applications in robotics of services based on industry 4.0 and cloud computing was carried out. The first part of the work consists of characterizing the elements of Industry 4.0 applicable to indoor service robotics. Once defined, the cloud computing models applicable to service robotics were identified, and then artificial intelligence techniques were incorporated to control the navigation of mobile robots in indoor environments. Afterwards, the elements of Industry 4.0 and cloud computing were integrated, for the autonomous navigation of a robotic system. With the above, a methodology was built, adding elements such as sensorics, locomotion, manipulation, web development, data sources, development environments in the cloud, simulation, control architectures, and visual fiducial markers. Finally, the proposed method was validated by carrying out a set of tests in a logistic setting, thereby generating results and conclusions.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Ingeniería de Sistemasspa
dc.description.researchareaRobótica de serviciosspa
dc.format.extentxvii, 133 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/80463
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.departmentDepartamento de la Computación y la Decisiónspa
dc.publisher.facultyFacultad de Minasspa
dc.publisher.placeMedellín, Colombiaspa
dc.publisher.programMedellín - Minas - Maestría en Ingeniería - Ingeniería de Sistemasspa
dc.relation.referencesBaalbaki, l., & Xie, X. (2009). A decision framework for operation management of reconfigurable mobile service robots in hospitals. IFAC Proceedings Volumes, 151-156.spa
dc.relation.referencesDeuseab, J. R. (2014). Methodology for the Planning and Implementation of Service Robotics in Industrial WorN Processes. Conference on Assembly Tecnologies and System, 41-46.spa
dc.relation.referencesDourado, C., da Silvaa, S., da Nóbrega, R., Barros, A., Sangaiah, A., Rebouças, P., . . . Victor. (2019). A new approach for mobile robot localization based on an online IoT system. Future Generation Computer Systems, 859-881.spa
dc.relation.referencesDröder, K., lBobka, P., Germann, T., Gabriel, F., & Dietrich, F. (2018). A Machine Learning-Enhanced Digital Twin Approach for Human-Robot-Collaboration. Procedia CIRP, 187-192.spa
dc.relation.referencesErboz, G. (2017). How To Define Industry 4.0: Main Pillars Of Industry 4.0. 7th International Conference on Management (pág. 9). Nitra: ICoM.spa
dc.relation.referencesFarinelli, A., Boscolo, N., Zanotto, E., & Pagello, E. (2017). Advanced approaches for multi-robot coordination in logistic scenarios. Robotics and Autonomous Systems, 34-44.spa
dc.relation.referencesGiusti Bravo, F. (13 de Septiembre de 2016). beetrack. Recuperado el 20 de Diciembre de 2019, de Robótica Industrial: una mirada actual y lo que viene: https://www.beetrack.com/es/blog/robotica-industrial-una-mirada-actual-y-lo-que-vienespa
dc.relation.referencesHehua, Y., Qingsong, H., Yingying, W., Wenguo, W., & Muhammad, I. (2017). Cloud robotics in Smart Manufacturing Environments: Challenges and countermeasures. Computers & Electrical Engineering, 56-62.spa
dc.relation.referencesJin, W., IlKwag, S., & DaeKo, Y. (2020). Optimal capacity and operation design of a robot logistics system for the hotel industry. Tourism Management, 103-971.spa
dc.relation.referencesKousi, N., Koukas, S., Michalos, G., Makris, S., & Chryssolouris, G. (2016). Service Oriented Architecture for Dynamic Scheduling of Mobile Robots for Material Supply. Procedia CIRP, 18-22.spa
dc.relation.referencesKuhner, D., Fiederer, L., & Aldingerad, J. (2019). A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain–computer interfacing. Robotics and Autonomous Systems, 98-113.spa
dc.relation.referencesLi, H., & Savkin, A. (2018). An algorithm for safe navigation of mobile robots by a sensor network in dynamic cluttered industrial environments. Robotics and Computer-Integrated Manufacturing, 65-82.spa
dc.relation.referencesMadrid, R. (19 de Octubre de 2019). Redaccion Medica. Obtenido de Robots: los nuevos ayudantes hospitalarios: https://www.redaccionmedica.com/noticia/los-robots-los-nuevos-ayudantes-hospitalarios-88603spa
dc.relation.referencesOzaki, K., Kagaya, H., & SatoshiHirano. (2013). Preliminary Trial of Postural Strategy Training Using a Personal Transport Assistance Robot for Patients With Central Nervous System Disorder. Archives of Physical Medicine and Rehabilitation, 59-66.spa
dc.relation.referencesRivera, Z., Simone, M., & Guida, D. (2019). Unmanned Ground Vehicle Modelling in Gazebo/ROS-Based Environments. Machines, 21.spa
dc.relation.referencesSchuessler, Z., Schuessler, H., & Strohaber, J. (2018). Robotic-assisted hysterectomy in a community hospital after seven years of experience. Laparoscopic, Endoscopic and Robotic Surgery, 42-45.spa
dc.relation.referencesVelagic.J, & Balta.H. (2010). Design and Development of Control and Communication Systems for Complex Mobile Robot and Manipulator Structure. IFAC Proceedings Volumes, 307-312.spa
dc.relation.referencesXiaa, C., Zhanga, Y., Wang, L., Coleman, S., & Liua, Y. (2018). Microservice-based cloud robotics system for intelligent space. Robotics and Autonomous Systems, 139-150.spa
dc.relation.referencesYan, H., Hua, Q., Wang, Y., Wei, W., & Imrand, M. (2017). Cloud robotics in Smart Manufacturing Environments: Challenges and countermeasures. Computers & Electrical Engineering, 56-65.spa
dc.relation.referencesYavasa, V., Deniz, Y., & Ozenb, Y. (2020). Logistics centers in the new industrial era: A proposed framework for logistics center 4.0. Transportation Research Part E: Logistics and Transportation Review, 101-864.spa
dc.relation.referencesZhu, D. (2018). IOT and big data based cooperative logistical delivery scheduling method and cloud robot system. Future Generation Computer Systems, 709-715.spa
dc.relation.referencesBhavsar, P., Patel, S., & Sobh, T. (2019). Hybrid Robot-as-a-Service (RaaS) Platform (Using MQTT and CoAP). International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (pág. 16). Atlanta: IEEE.spa
dc.relation.referencesD. Bogataj, D. B. (2019). The ageing workforce challenge: investments in collaborative robots or contribution to pension schemes, from the multi-echelon perspective. International Journal of Production Economics, 106.spa
dc.relation.referencesGonzales, p., Calvo, I., Etxberria, I., & Zulueta, E. (2015). Hacia un framework basado en ROS para la implementación de Sistemas. Jornadas de Automática,, (págs. 1050-1057). Bilbao.spa
dc.relation.referencesJ. Guiochet, M. M. (2017). Safety-critical advanced robots: a survey. Rob Auton Syst, 52.spa
dc.relation.referencesOMRON. (2019). OMRON Automatizacion Industrial. Obtenido de industrial omron: https://industrial.omron.es/spa
dc.relation.referencesPyo, Y., Nakashima, K., & Kuwahata, S. (2015). Service robot system with an informationally structured environment. Robotics and autonomous System, 148-165.spa
dc.relation.referencesSadek, L., & Ayad, S. (2015). TOWARDS A NEW CLOUD ROBOTICS APPROACH. Proceedings of the 8th International Symposium on Mechatronics and its Applications (ISMA12) (pág. 5). Sharjah: UAE.spa
dc.relation.referencesSakamoto, J., Kiyoyama, K., Matsumoto, K., & Pyo, Y. (2018). Development of ROS-TMS 5.0 for informationally structured environment. ROBOMETCH JOURNAL.spa
dc.relation.referencesSchumann, H. (25 de Junio de 2018). ZIVID. Obtenido de https://blog.zivid.comspa
dc.relation.referencesToris, R., Kent, D., & Chernova, S. (2014). Toris, R., Kent, D., & Chernova, S. (2014). The robot management system: a framework for conducting human-robot interaction studies through crowdsourcing. HRI 2014. HRI, (pág. 16).spa
dc.relation.referencesUllah, l. (2019). Modeling and simulation of complex manufacturing phenomena using sensor signals from the perspective of Industry 4.0. En C. Chen, & T. Hartmann, Advanced Engineering Informatics (pág. 358). ScienceDirect.spa
dc.relation.referencesHu, G., Peng, W., & Wen, Y. (2012). Cloud Robotics:Architecture, Challenges and Applications. IEEE Network , 21-28.spa
dc.relation.referencesKoubaa, A. (2014). A Service-Oriented Architecture for Virtualizing. International Conference on Architecture of Computing Systems, 196-208.spa
dc.relation.referencesMbunge, E., Fashoto, S., & Dlamini, S. (2020). Modelling a Gossip-based Protocol for Enhanced Dynamic Routing. asian journal of information tecnology, 203-206.spa
dc.relation.referencesYoon, J., & Park, H. (2015). A Cloud-based Integrated Development Environment for robot software Development. Journal of Institute of Control, Robotics and Systems, 173-178.spa
dc.relation.referencesA General Framework for Temporal Calibration of Multiple Proprioceptive and Exteroceptive Sensors. (2014). En J. Kelly, & G. S. Sukhatme, Experimental Robotics (págs. 195-209). Springer.spa
dc.relation.referencesA. Batlle, J., & Barjau, A. (2009). Holonomy in mobile robots. Robotics and Autonomous Systems .spa
dc.relation.referencesAcosta, G., Gallardo, j., & Perez, R. (2016). Reactive control architecture for autonomous mobile robot navigation. Revista Chilena de Ingenieria.spa
dc.relation.referencesAlmasri, M., Elleithy, K., & Alajlan, A. (2016). Sensor Fusion Based Model for Collision Free Mobile Robot Navigation. Sensors, 16-24.spa
dc.relation.referencesAndreev, A., & Peregudova, O. (2020). On global trajectory tracking control of robot manipulators in cylindrical phase space. International Journal of Control, 3003-3015.spa
dc.relation.referencesB.S.K.K, I., & Ahmed, M. (2014). Modelling and Control of SCARA Manipulator. Procedia Computer Science, 106-113.spa
dc.relation.referencesBambino, i. (2008). Una Introducción a los Robots Móviles .spa
dc.relation.referencesBarrientos Sotelo, V. R., García Sánchez, J. R., & Silva Ortigoza, R. (2007). Robots Móviles: Evolución y Estado del Arte. Polibits, 12-17.spa
dc.relation.referencesBarrientos, A., Peñin, L. F., Balaguer, C., & Aracil, R. (1997). Fundamentos de Robotica. Madrid: McGraw-Hill.spa
dc.relation.referencesCardoso, E., Fernandez, A., Marrero-Osorio, S. A., & Guardado, P. (2017). Modelos cinemático y dinámico de un robot de cuatro grados de libertad. Ingeniería Electrónica, Automática y Comunicaciones, 56-75.spa
dc.relation.referencesCrick, C., Jay, G., Osentoski, S., Pitzer, B., & Jenkins, O. C. (2017). Rosbridge: ROS for Non-ROS Users. En H. I. Christensen, & O. Khatib, Robotics Research (págs. 493-504). Switzerland: Springer International Publishing.spa
dc.relation.referencesDikra, E., Badreddine, A., Larbi, E., & Jalal, E. (2019). Optimal Trajectory Planning for Spherical Robot Using Evolutionary Algorithms. Procedia Manufacturing, 960-968.spa
dc.relation.referencesFiala, M. (2005). ARTag, a fiducial marker system using digital techniques. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) (págs. 590-596). IEEE.spa
dc.relation.referencesGea, M., & Gutierrez, l. (2002). La interacción persona-ordenador. Granada: Universidad de Granada.spa
dc.relation.referencesGoergen, R., Maboni, M., & Gioppo de Souza, M. (2018). Design of an Experimental Workbench for Force Control Tests with Pneumatic Actuators. Proposal of an Autonomous System for Inspection of Structures (págs. 52-57). São Paulo: ABIMAQ.spa
dc.relation.referencesHrbáček, J., Ripel, T., & Krejsa, J. (2010). Ackermann mobile robot chassis with independent rear wheel drives. Power Electronics and Motion Control Conference (EPE/PEMC), 2010 14th International.spa
dc.relation.referencesKabanov, A., & Balabanov, A. (2018). The modeling of an anthropomorphic robot arm. International Conference on Modern Trends in Manufacturing Technologies and Equipment (ICMTMTE 2018).spa
dc.relation.referencesMandow, A., Martínez, J. L., Morales, J., & Blanco, J. L. (2007). Experimental kinematics for wheeled skid-steer mobile robots. Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International, (págs. 1222-1227).spa
dc.relation.referencesMcTaggart, M. &.-B., Razjigaev, A., Rowntree, T., Vijay, K., Wade-McCue, S., & Tow, A. (2017). Mechanical Design of a Cartesian Manipulator for Warehouse Pick and Place. arxiv.spa
dc.relation.referencesMohd Annuar, K., & Sapiee, M. (2018). Synchronous Mobile Robots Formation Control. TELKOMNIKA Indonesian Journal of Electrical Engineering. 16.spa
dc.relation.referencesNavegación en Robots. (2011). En Y. Torres, & A. Ines, Planificacion de trayectorias en robots mobiles (págs. 21-52).spa
dc.relation.referencesNielsen, I., Dang, Q.-V., Bocewicz, G., & Banaszak, Z. (2017). A methodology for Implementation of Mobile Robot in Adaptive Manufacturing Environments. Journal of Intelligent Manufacturing, (págs. 1171 - 1188).spa
dc.relation.referencesprofander, S. (2014). Implementation and Evaluation of multimodal input/output channels for task-based industrial robot programming.spa
dc.relation.referencesRamirez Arias, J. L., Fonseca, R., & Astrid. (2012). Mathematical modeling of the direct. Revista Ingeniería Solidaria, vol. 8, 46-52.spa
dc.relation.referencesRiaño, C., Peña, C., & Sánchez, H. (2018). Aplicación de técnicas de desenvolvimiento de producto para el desarrollo de un robot antropomórfico. Revista UIS Ingenierías , 21-34.spa
dc.relation.referencesRojas, D. B., Lorente, L. E., & de Quirós, C. B. (2002). Planificación local basada en sensores para un manipulador móvil en tareas de colaboración con humanos. Madrid: Universidad Carlos III de Madrid.spa
dc.relation.referencesRossmann, J., Ruf, H., & Schlette, C. (2009). Model-Based Programming “by Demonstration”– Fast Setup of Robot Systems (ProDemo). En T. Kroger, & F. Wahl, Advances in Robotics Research: Theory, Implementation, Application (págs. 159-168). Springer.spa
dc.relation.referencesRubio, f., Valero, F., & Llopis, C. (2019). A review of mobile robots: Concepts, methods, theoretical framework, and applications. International Journal of Advance Robotic Systems.spa
dc.relation.referencesRuiz, J. (2016). Probabilistic Techniques in Semantic. malaga: Universidad de malaga.spa
dc.relation.referencesSalter, T., Michaud, F., Létourneau, D., Lee, D., & Werry, I. (2007). Using proprioceptive sensors for categorizing human-robot interactions. 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI). Arlington: IEEE.spa
dc.relation.referencesSanders, D. (2008). Environmental sensors and networks of sensors. Sensor Review.spa
dc.relation.referencesSungBu, K., I.O.Lee, D.I.Cho, & JangMyung, L. (2006). DYNAMIC LOCALIZATION OF A MOBILE ROBOT WITH ACTIVE BEACON SENSORS. IFAC Proceedings Volumes, 921-925.spa
dc.relation.referencesTerakawa, T., Komori, M., & Matsuda, K. (2019). Motion Analysis of an Omnidirectional Mobile Robot with Wheels Connected by Passive Sliding Joints. Advances in Mechanism and Machine Science , 2279-2288.spa
dc.relation.referencesVinh, Q., Ewa, I., Bøgh, S., & Bocewicz, G. (2013). Modelling and Scheduling Autonomous Mobile Robot for a Real-World Industrial Application. IFAC Conference on Manufacturing Modelling, Management and Control. Russia.spa
dc.relation.referencesZenatti, F., Fontanelli, D., Palopoli, L., Macii, D., & Nazemzadeh, P. (2016). Optimal placement of passive sensors for robot localization. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-CompartirIgual 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/spa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computaciónspa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::003 - Sistemasspa
dc.subject.lembRobóticaspa
dc.subject.lembRoboticseng
dc.subject.lembInteligencia artificialspa
dc.subject.proposalIndustria 4.0spa
dc.subject.proposalComputación en la nubespa
dc.subject.proposalMarcadores fiducialesspa
dc.subject.proposalArquitectura de controlspa
dc.subject.proposalLocomociónspa
dc.subject.proposalIndustry 4.0eng
dc.subject.proposalCloud computingeng
dc.subject.proposalFiducial markerseng
dc.subject.proposalControl architectureeng
dc.titleMétodo para el desarrollo de aplicaciones en robótica de servicios basados en industria 4.0 y computación en la nube.spa
dc.title.translatedMethod for the development of applications in robotics of services based on industry 4.0 and cloud computing.eng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

Archivos

Bloque original

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
1035431163.2021.pdf
Tamaño:
4.28 MB
Formato:
Adobe Portable Document Format
Descripción:
Tesis Maestría en Ingeniería - Ingeniería de Sistemas

Bloque de licencias

Mostrando 1 - 1 de 1
No hay miniatura disponible
Nombre:
license.txt
Tamaño:
3.87 KB
Formato:
Item-specific license agreed upon to submission
Descripción: