A LabVIEW-based autonomous vehicle navigation system using robot vision and fuzzy control
This paper describes a navigation system for an autonomous vehicle using machine vision techniques applied to real-time captured images of the track, for academic purposes. The experiment consists of the automatic navigation of a remote control car through a closed circuit. Computer vision technique...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2011 |
| País: | México |
| Institución: | Instituto Nacional de Astrofísica, Óptica y Electrónica |
| Repositorio: | Repositorio Institucional del INAOE |
| Idioma: | inglés |
| OAI Identifier: | oai:inaoe.repositorioinstitucional.mx:1009/1743 |
| Acceso en línea: | http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1743 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/Fuzzy/Fuzzy info:eu-repo/classification/Control/Control info:eu-repo/classification/Robot/Robot info:eu-repo/classification/Vision/Vision info:eu-repo/classification/Autonomous/Autonomous info:eu-repo/classification/Navigation/Navigation info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/22 info:eu-repo/classification/cti/2203 |
| Sumario: | This paper describes a navigation system for an autonomous vehicle using machine vision techniques applied to real-time captured images of the track, for academic purposes. The experiment consists of the automatic navigation of a remote control car through a closed circuit. Computer vision techniques are used for the sensing of the environment through a wireless camera. The received images are captured into the computer through the acquisition card NI USB-6009, and processed in a system developed under the LabVIEW platform, taking advantage of the toolkit for acquisition and image processing. Fuzzy logic control techniques are incorporated for the intermediate control decisions required during the car navigation. An e cient approach based on logic machine-states is used as an optimal method to implement the changes required by the fuzzy logic control. Results and concluding remarks are presented. |
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