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Autonavi3at Software Interface to Autonomously Navigate on Urban Roads Using Omnidirectional Vision and a Mobile Robot

Interfaz de software Autonavi3at para navegar de forma autónoma en vías urbanas mediante visión omnidireccional y un robot móvil

dc.creatorCaicedo Martínez, Jorge Enrique
dc.creatorBacca Cortes, Bladimir
dc.date2022-06-03
dc.date2023-03-22T18:49:16Z
dc.date2023-03-22T18:49:16Z
dc.date.accessioned2026-03-25T19:32:44Z
dc.date.available2026-03-25T19:32:44Z
dc.identifierhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/5724
dc.identifier10.18359/rcin.5724
dc.identifierhttps://hdl.handle.net/10654/42621
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/201844
dc.descriptionThe design of efficient autonomous navigation systems for mobile robots or autonomous vehicles is fundamental to perform the programmed tasks. Basically, two kind of sensors are used in urban road following: LIDAR and cameras. LIDAR sensors are highly accurate but expensive and extra work is needed for human understanding of the point cloud scenes; however, visual content is understood better by human beings, which should be used to develop human-robot interfaces. In this work, a computer vision-based urban road following software tool called AutoNavi3AT for mobile robots and autonomous vehicles is presented. The urban road following scheme proposed in AutoNavi3AT uses vanishing point estimation and tracking on panoramic images to control the mobile robot heading on the urban road. To do that, Gabor filters, region growing, and particle filters were used. In addition, laser range data are also employed for local obstacle avoidance. Quantitative results were achieved using two kind of tests, one uses datasets acquired at the Universidad del Valle campus, and field tests using a Pioneer 3AT mobile robot. As a result, important improvements in the vanishing point estimation of 68.26 % and 61.46 % in average were achieved, which is useful for mobile robots and autonomous vehicles when they are moving on urban roads.
dc.descriptionEl diseño de sistemas de navegación autónomos eficientes para robots móviles o vehículos autónomos es fundamental para realizar las tareas programadas. Básicamente, se utilizan dos tipos de sensores en el seguimiento de vías urbanas: LIDAR y cámaras. Los sensores LIDAR son muy precisos, pero costosos y se necesita trabajo adicional para la comprensión humana de las escenas de nubes de puntos; sin embargo, los seres humanos entienden mejor el contenido visual, lo que debería usarse para desarrollar interfaces humano-robot. En este trabajo, se presenta una herramienta de software de seguimiento de carreteras urbanas basada en visión artificial llamada AutoNavi3AT para robots móviles y vehículos autónomos. El esquema de seguimiento de vías urbanas propuesto en AutoNavi3AT utiliza la estimación del punto de fuga y el seguimiento de imágenes panorámicas para controlar el avance del robot móvil en la vía urbana. Para ello se utilizaron filtros Gabor, crecimiento de regiones y filtros de partículas. Además, los datos de alcance del láser también se emplean para evitar obstáculos locales. Los resultados cuantitativos se lograron utilizando dos tipos de pruebas, una utiliza conjuntos de datos adquiridos en el campus de la Universidad del Valle y pruebas de campo utilizando un robot móvil Pioneer 3AT. Como resultado, se lograron mejoras importantes en la estimación del punto de fuga de 68.26% y 61.46% en promedio, lo cual es útil para robots móviles y vehículos autónomos cuando se desplazan por vías urbanas.
dc.formatapplication/pdf
dc.formattext/xml
dc.languageeng
dc.publisherUniversidad Militar Nueva Granada
dc.relationhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/5724/5115
dc.relationhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/5724/5188
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dc.rightsDerechos de autor 2022 Ciencia e Ingeniería Neogranadina
dc.sourceCiencia e Ingenieria Neogranadina; Vol. 32 No. 1 (2022); 99-113
dc.sourceCiencia e Ingeniería Neogranadina; Vol. 32 Núm. 1 (2022); 99-113
dc.sourceCiencia e Ingeniería Neogranadina; v. 32 n. 1 (2022); 99-113
dc.source1909-7735
dc.source0124-8170
dc.subjectomnidirectional vision
dc.subjectvanishing points
dc.subjectparticle filter
dc.subjectautonomous vehicles
dc.subjectvisión omnidireccional
dc.subjectpuntos de fuga
dc.subjectfiltros de particulas
dc.subjectvehículos autónomos
dc.titleAutonavi3at Software Interface to Autonomously Navigate on Urban Roads Using Omnidirectional Vision and a Mobile Robot
dc.titleInterfaz de software Autonavi3at para navegar de forma autónoma en vías urbanas mediante visión omnidireccional y un robot móvil
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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