Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow
This document presents the proposal for the design and implementation of a trajectory tracking algorithm that will be incorporated into the flight control system of the Parrot Mambo minidrone, with the aim of performing autonomous flights. The tracking algorithm will be developed in three phases: in...
- Autores:
-
Trujillo Loaiz, Estive Leandro
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2022
- Institución:
- Universidad Antonio Nariño
- Repositorio:
- Repositorio UAN
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uan.edu.co:123456789/7269
- Acceso en línea:
- http://repositorio.uan.edu.co/handle/123456789/7269
- Palabra clave:
- UAVs,
RC,
Algoritmo,
Imagen,
Resolución,
RGB,
coordenadas.
UAVs,
RC,
Algorithm,
Image,
Resolution,
RGB,
coordinates
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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| dc.title.es_ES.fl_str_mv |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| title |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| spellingShingle |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow UAVs, RC, Algoritmo, Imagen, Resolución, RGB, coordenadas. UAVs, RC, Algorithm, Image, Resolution, RGB, coordinates |
| title_short |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| title_full |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| title_fullStr |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| title_full_unstemmed |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| title_sort |
Diseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/Stateflow |
| dc.creator.fl_str_mv |
Trujillo Loaiz, Estive Leandro |
| dc.contributor.advisor.spa.fl_str_mv |
Erazo Ordoñez, Christian |
| dc.contributor.author.spa.fl_str_mv |
Trujillo Loaiz, Estive Leandro |
| dc.subject.es_ES.fl_str_mv |
UAVs, RC, Algoritmo, Imagen, Resolución, RGB, coordenadas. |
| topic |
UAVs, RC, Algoritmo, Imagen, Resolución, RGB, coordenadas. UAVs, RC, Algorithm, Image, Resolution, RGB, coordinates |
| dc.subject.keyword.es_ES.fl_str_mv |
UAVs, RC, Algorithm, Image, Resolution, RGB, coordinates |
| description |
This document presents the proposal for the design and implementation of a trajectory tracking algorithm that will be incorporated into the flight control system of the Parrot Mambo minidrone, with the aim of performing autonomous flights. The tracking algorithm will be developed in three phases: initially a sequence of images will be processed through three processes that are; binarization, segmentation, and pixel counting, then the algorithm will be designed through the design of the state machine for data acquisition and processing and finally the algorithm will be validated through Simulink/Stateflow considering four scenarios where it will be tested the performance. Likewise, in the development of this document, an effectiveness of 93.33% success was demonstrated in the different performance tests of the algorithm, and part of the efficiency is presented in the data collection, the pulses emitted by the different sensors that were generated from the image, the duration of each pulse is variable and can range from 9 s to end at 18 s, and the response time seen in the final movement of the drone lasts exactly the time that the pulses take |
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2022 |
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2022-11-15T22:36:51Z |
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2022-11-15T22:36:51Z |
| dc.date.issued.spa.fl_str_mv |
2022-07-26 |
| dc.type.spa.fl_str_mv |
Trabajo de grado (Pregrado y/o Especialización) |
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http://purl.org/coar/resource_type/c_7a1f |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_7a1f |
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http://repositorio.uan.edu.co/handle/123456789/7269 |
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[1] T. de Swarte, O. Boufous, and P. Escalle, “Artificial intelligence, ethics and human values: the cases of military drones and companion robots,” Artif. Life Robot., vol. 24, no. 3, pp. 291–296, 2019, doi: 10.1007/s10015-019-00525-1. [2] H. Zimmermann, L. Vidiasova, I. Tensina, and C. Lee, Electronic Governance and Open Society: Challenges in Eurasia, vol. 947. 2019. [3] V. Sgurev, V. Piuri, and V. Jotsov, Learning Systems: From Theory to Practice, vol. 756. 2018. [4] “¿QUÉ TIPOS DE DRONES EXISTEN? - areadron.com.” https://www.areadron.com/que-tipos-de-drones-existen/ (accessed Oct. 13, 2020). [5] “Support - Parrot Mambo Fly | Sitio Web Official de Parrot.” https://support.parrot.com/es/support/productos/parrot-mambo-fly (accessed Nov. 02, 2020). [6] B. Demir et al., “Real-time high-resolution omnidirectional imaging platform for drone detection and tracking,” J. Real-Time Image Process., vol. 17, no. 5, pp. 1625– 1635, 2020, doi: 10.1007/s11554-019-00921-7. [7] R. Collins, X. Zhou, and S. K. Teh, “An Open Source Tracking Testbed and Evaluation Web Site,” IEEE Int. Work. Perform. Eval. Track. Surveill., vol. 5, pp. 3769–3772, 2005. [8] Y. G. Han, S. H. Jung, and O. Kwon, “How to utilize vegetation survey using drone image and image analysis software,” J. Ecol. Environ., vol. 41, no. 1, pp. 1–6, 2017, doi: 10.1186/s41610-017-0035-2. [9] J. Fleureau, Q. Galvane, F. L. Tariolle, and P. Guillotel, “Generic drone control platform for autonomous capture of cinema scenes,” DroNet 2016 - Proc. 2nd Work. Micro Aer. Veh. Networks, Syst. Appl. Civ. Use, co-located with MobiSys 2016, pp. 35–40, 2016, doi: 10.1145/2935620.2935622. [10] T. Nageli, J. Alonso-Mora, A. Domahidi, D. Rus, and O. Hilliges, “Real-time motion planning for aerial videography with real-time with dynamic obstacle avoidance and viewpoint optimization,” IEEE Robot. Autom. Lett., vol. 2, no. 3, pp. 1696–1703, 2017, doi: 10.1109/LRA.2017.2665693. |
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instname:Universidad Antonio Nariño |
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[1] T. de Swarte, O. Boufous, and P. Escalle, “Artificial intelligence, ethics and human values: the cases of military drones and companion robots,” Artif. Life Robot., vol. 24, no. 3, pp. 291–296, 2019, doi: 10.1007/s10015-019-00525-1. [2] H. Zimmermann, L. Vidiasova, I. Tensina, and C. Lee, Electronic Governance and Open Society: Challenges in Eurasia, vol. 947. 2019. [3] V. Sgurev, V. Piuri, and V. Jotsov, Learning Systems: From Theory to Practice, vol. 756. 2018. [4] “¿QUÉ TIPOS DE DRONES EXISTEN? - areadron.com.” https://www.areadron.com/que-tipos-de-drones-existen/ (accessed Oct. 13, 2020). [5] “Support - Parrot Mambo Fly | Sitio Web Official de Parrot.” https://support.parrot.com/es/support/productos/parrot-mambo-fly (accessed Nov. 02, 2020). [6] B. Demir et al., “Real-time high-resolution omnidirectional imaging platform for drone detection and tracking,” J. Real-Time Image Process., vol. 17, no. 5, pp. 1625– 1635, 2020, doi: 10.1007/s11554-019-00921-7. [7] R. Collins, X. Zhou, and S. K. Teh, “An Open Source Tracking Testbed and Evaluation Web Site,” IEEE Int. Work. Perform. Eval. Track. Surveill., vol. 5, pp. 3769–3772, 2005. [8] Y. G. Han, S. H. Jung, and O. Kwon, “How to utilize vegetation survey using drone image and image analysis software,” J. Ecol. Environ., vol. 41, no. 1, pp. 1–6, 2017, doi: 10.1186/s41610-017-0035-2. [9] J. Fleureau, Q. Galvane, F. L. Tariolle, and P. Guillotel, “Generic drone control platform for autonomous capture of cinema scenes,” DroNet 2016 - Proc. 2nd Work. Micro Aer. Veh. Networks, Syst. Appl. Civ. Use, co-located with MobiSys 2016, pp. 35–40, 2016, doi: 10.1145/2935620.2935622. [10] T. Nageli, J. Alonso-Mora, A. Domahidi, D. Rus, and O. Hilliges, “Real-time motion planning for aerial videography with real-time with dynamic obstacle avoidance and viewpoint optimization,” IEEE Robot. Autom. Lett., vol. 2, no. 3, pp. 1696–1703, 2017, doi: 10.1109/LRA.2017.2665693. instname:Universidad Antonio Nariño reponame:Repositorio Institucional UAN repourl:https://repositorio.uan.edu.co/ |
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Universidad Antonio Nariño |
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Ingeniería Mecatrónica |
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Facultad de Ingeniería Mecánica, Electrónica y Biomédica |
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Bogotá - Sur |
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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)Acceso abiertohttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Erazo Ordoñez, ChristianTrujillo Loaiz, Estive Leandro11481623983Colombia(Bogotá,Dc)2022-11-15T22:36:51Z2022-11-15T22:36:51Z2022-07-26http://repositorio.uan.edu.co/handle/123456789/7269[1] T. de Swarte, O. Boufous, and P. Escalle, “Artificial intelligence, ethics and human values: the cases of military drones and companion robots,” Artif. Life Robot., vol. 24, no. 3, pp. 291–296, 2019, doi: 10.1007/s10015-019-00525-1.[2] H. Zimmermann, L. Vidiasova, I. Tensina, and C. Lee, Electronic Governance and Open Society: Challenges in Eurasia, vol. 947. 2019.[3] V. Sgurev, V. Piuri, and V. Jotsov, Learning Systems: From Theory to Practice, vol. 756. 2018.[4] “¿QUÉ TIPOS DE DRONES EXISTEN? - areadron.com.” https://www.areadron.com/que-tipos-de-drones-existen/ (accessed Oct. 13, 2020).[5] “Support - Parrot Mambo Fly | Sitio Web Official de Parrot.” https://support.parrot.com/es/support/productos/parrot-mambo-fly (accessed Nov. 02, 2020).[6] B. Demir et al., “Real-time high-resolution omnidirectional imaging platform for drone detection and tracking,” J. Real-Time Image Process., vol. 17, no. 5, pp. 1625– 1635, 2020, doi: 10.1007/s11554-019-00921-7.[7] R. Collins, X. Zhou, and S. K. Teh, “An Open Source Tracking Testbed and Evaluation Web Site,” IEEE Int. Work. Perform. Eval. Track. Surveill., vol. 5, pp. 3769–3772, 2005.[8] Y. G. Han, S. H. Jung, and O. Kwon, “How to utilize vegetation survey using drone image and image analysis software,” J. Ecol. Environ., vol. 41, no. 1, pp. 1–6, 2017, doi: 10.1186/s41610-017-0035-2.[9] J. Fleureau, Q. Galvane, F. L. Tariolle, and P. Guillotel, “Generic drone control platform for autonomous capture of cinema scenes,” DroNet 2016 - Proc. 2nd Work. Micro Aer. Veh. Networks, Syst. Appl. Civ. Use, co-located with MobiSys 2016, pp. 35–40, 2016, doi: 10.1145/2935620.2935622.[10] T. Nageli, J. Alonso-Mora, A. Domahidi, D. Rus, and O. Hilliges, “Real-time motion planning for aerial videography with real-time with dynamic obstacle avoidance and viewpoint optimization,” IEEE Robot. Autom. Lett., vol. 2, no. 3, pp. 1696–1703, 2017, doi: 10.1109/LRA.2017.2665693.instname:Universidad Antonio Nariñoreponame:Repositorio Institucional UANrepourl:https://repositorio.uan.edu.co/This document presents the proposal for the design and implementation of a trajectory tracking algorithm that will be incorporated into the flight control system of the Parrot Mambo minidrone, with the aim of performing autonomous flights. The tracking algorithm will be developed in three phases: initially a sequence of images will be processed through three processes that are; binarization, segmentation, and pixel counting, then the algorithm will be designed through the design of the state machine for data acquisition and processing and finally the algorithm will be validated through Simulink/Stateflow considering four scenarios where it will be tested the performance. Likewise, in the development of this document, an effectiveness of 93.33% success was demonstrated in the different performance tests of the algorithm, and part of the efficiency is presented in the data collection, the pulses emitted by the different sensors that were generated from the image, the duration of each pulse is variable and can range from 9 s to end at 18 s, and the response time seen in the final movement of the drone lasts exactly the time that the pulses takeEn este documento se presenta la propuesta de diseño e implementación de un algoritmo de seguimiento de trayectorias que se incorporará al sistema de control de vuelo del minidrone Parrot Mambo, con el objetivo de realizar vuelos autónomos. El algoritmo de seguimiento se desarrollará en tres fases: inicialmente se procesará una secuencia de imágenes por medio de tres procesos que son; binarización, segmentación, y conteo de pixeles, luego se diseñará el algoritmo por medio del diseño de la máquina de estados para la adquisición y procesamiento de datos y finalmente se validará el algoritmo a través de Simulink/Stateflow considerando cuatro escenarios donde se pondrá a prueba el funcionamiento. Asimismo en el desarrollo de este documento se observó una efectividad del 93.33% de éxito en las diferentes pruebas de rendimiento del algoritmo, y parte de la eficiencia se presenta en la recolección de datos los pulsos emitidos por los distintos sensores que se generaron a partir de la imagen, la duración de cada pulsación es variable y puede rondar desde 9 s hasta finalizar a los 18 s, y el tiempo de respuesta visto en el movimiento final del dron dura exactamente el tiempo que demoran los pulsosIngeniero(a) Mecatrónico(a)PregradoPresencialInvestigaciónspaUniversidad Antonio NariñoIngeniería MecatrónicaFacultad de Ingeniería Mecánica, Electrónica y BiomédicaBogotá - SurUAVs,RC,Algoritmo,Imagen,Resolución,RGB,coordenadas.UAVs,RC,Algorithm,Image,Resolution,RGB,coordinatesDiseño e implementación de un algoritmo de seguimiento de trayectorias para el minidron Parrot mambo utilizando – Simulink/StateflowTrabajo de grado (Pregrado y/o Especialización)http://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85GeneralORIGINAL2022_ Acta_EstiveTrujillo.pdf2022_ Acta_EstiveTrujillo.pdfActa de sustentaciónapplication/pdf172833https://repositorio.uan.edu.co/bitstreams/39672bcd-5811-4101-b07b-3af0a180356c/download1738af40aefb65c1bf73070e0c771ec2MD512022_TG EstiveTrujillo.pdf2022_TG EstiveTrujillo.pdfTrabajo de gradoapplication/pdf3820265https://repositorio.uan.edu.co/bitstreams/dd6c9108-2ddf-451d-9999-2155ccd17c3b/download8ba1bfe84a4aef21dcb7ff4394108013MD522022_Autorización.pdf2022_Autorización.pdfAutorización de autoresapplication/pdf634803https://repositorio.uan.edu.co/bitstreams/dc5c4592-b2b9-491c-8edc-b186ef528792/download6e0dede3dd2ff6b8917d87e0f92645edMD53CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.uan.edu.co/bitstreams/db13f900-8a3a-4fc9-9413-7cfe97685025/download9868ccc48a14c8d591352b6eaf7f6239MD54123456789/7269oai:repositorio.uan.edu.co:123456789/72692024-10-09 23:08:54.099https://creativecommons.org/licenses/by-nc-nd/4.0/Acceso abiertorestrictedhttps://repositorio.uan.edu.coRepositorio Institucional UANalertas.repositorio@uan.edu.co |