Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System
This paper presents a method based on static patterns for robotic navigation using computer vision techniques implemented on CMUcam3 embedded system, also presents an analysis of computational complexity for this embedded system. The pattern to be determined is a black line with intersections, drivi...
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| Format: | Article |
| Language: | English |
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Instituto Tecnológico Metropolitano
2013-11-01
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| Series: | TecnoLógicas |
| Subjects: | |
| Online Access: | http://itmojs.itm.edu.co/index.php/tecnologicas/article/view/480 |
| _version_ | 1819070576366452736 |
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| author | Víctor M. Jurado-Gutierrez Juan S. Botero-Valencia Sergio I. Serna-Garcés Carlos A. Madrigal-Gonzalez |
| author_facet | Víctor M. Jurado-Gutierrez Juan S. Botero-Valencia Sergio I. Serna-Garcés Carlos A. Madrigal-Gonzalez |
| author_sort | Víctor M. Jurado-Gutierrez |
| collection | DOAJ |
| description | This paper presents a method based on static patterns for robotic navigation using computer vision techniques implemented on CMUcam3 embedded system, also presents an analysis of computational complexity for this embedded system. The pattern to be determined is a black line with intersections, driving the robotic agent over the line. A segmentation algorithm based in threshold is used after the images acquisition by the CMUcam3, then defines the thinning patterns and then the linear Hough transform is applied to determine the lines, the angles and the type of the intersections. Due to the linear Hough transform is a method that requires high processing, in this project, the range of the angles are limited and the accumulation space is normalized. The results showthat the method developed for the navigation is accurate and reliable, because in 87% of the decision segments it could determine correctly the type of intersection and the correction angle. The CMUcam3 embedded system succeeded to process an image between 0.15 and 0.28 seconds, depending of the type of the intersection. |
| first_indexed | 2024-12-21T17:08:08Z |
| format | Article |
| id | doaj.art-e5be0c3ca1c74255a80fc6fe4cb1b8ba |
| institution | Directory Open Access Journal |
| issn | 0123-7799 2256-5337 |
| language | English |
| last_indexed | 2024-12-21T17:08:08Z |
| publishDate | 2013-11-01 |
| publisher | Instituto Tecnológico Metropolitano |
| record_format | Article |
| series | TecnoLógicas |
| spelling | doaj.art-e5be0c3ca1c74255a80fc6fe4cb1b8ba2022-12-21T18:56:29ZengInstituto Tecnológico MetropolitanoTecnoLógicas0123-77992256-53372013-11-0100617629419Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded SystemVíctor M. Jurado-Gutierrez0Juan S. Botero-Valencia1Sergio I. Serna-Garcés2Carlos A. Madrigal-Gonzalez3Instituto Tecnológico Metropolitano, MedellínInstituto Tecnológico Metropolitano, MedellínInstituto Tecnológico Metropolitano, MedellínInstituto Tecnológico Metropolitano, MedellínThis paper presents a method based on static patterns for robotic navigation using computer vision techniques implemented on CMUcam3 embedded system, also presents an analysis of computational complexity for this embedded system. The pattern to be determined is a black line with intersections, driving the robotic agent over the line. A segmentation algorithm based in threshold is used after the images acquisition by the CMUcam3, then defines the thinning patterns and then the linear Hough transform is applied to determine the lines, the angles and the type of the intersections. Due to the linear Hough transform is a method that requires high processing, in this project, the range of the angles are limited and the accumulation space is normalized. The results showthat the method developed for the navigation is accurate and reliable, because in 87% of the decision segments it could determine correctly the type of intersection and the correction angle. The CMUcam3 embedded system succeeded to process an image between 0.15 and 0.28 seconds, depending of the type of the intersection.http://itmojs.itm.edu.co/index.php/tecnologicas/article/view/480Visión artificial, CMUcam3, transformada de Hough, sistema embebido. |
| spellingShingle | Víctor M. Jurado-Gutierrez Juan S. Botero-Valencia Sergio I. Serna-Garcés Carlos A. Madrigal-Gonzalez Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System TecnoLógicas Visión artificial, CMUcam3, transformada de Hough, sistema embebido. |
| title | Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System |
| title_full | Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System |
| title_fullStr | Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System |
| title_full_unstemmed | Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System |
| title_short | Robotic Navigation based in Statics Patterns using the CMUcam3 Embedded System |
| title_sort | robotic navigation based in statics patterns using the cmucam3 embedded system |
| topic | Visión artificial, CMUcam3, transformada de Hough, sistema embebido. |
| url | http://itmojs.itm.edu.co/index.php/tecnologicas/article/view/480 |
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