Design of a visual servoing control strategy for a 4WD4WS path tracking robot in an agricultural field
Descripción del Articulo
The search for automating agricultural tasks realization with the objective of increasing productivity and improving the exploit of resources using a ground mobile robot, arises the motivation to propose in the present thesis work, a visual servoing control strategy for the robot’s movement control...
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| Formato: | tesis de maestría |
| Fecha de Publicación: | 2025 |
| Institución: | Pontificia Universidad Católica del Perú |
| Repositorio: | PUCP-Tesis |
| Lenguaje: | inglés |
| OAI Identifier: | oai:tesis.pucp.edu.pe:20.500.12404/31842 |
| Enlace del recurso: | http://hdl.handle.net/20.500.12404/31842 |
| Nivel de acceso: | acceso embargado |
| Materia: | Robots móviles--Diseño Robots móviles--Sistemas de control Servomecanismos Procesamiento de imágenes Agricultura--Innovaciones tecnológicas https://purl.org/pe-repo/ocde/ford#2.00.00 |
| Sumario: | The search for automating agricultural tasks realization with the objective of increasing productivity and improving the exploit of resources using a ground mobile robot, arises the motivation to propose in the present thesis work, a visual servoing control strategy for the robot’s movement control over ridges in strawberry crop fields. In other words, the controller only uses a camera’s captured images for the robot’s path following. This robot has a four-wheel drive fourwheel steering (4WD4WS) structure on which the camera is mounted. For trajectory recognition, a U-Net convolutional neural network previously trained is used to perform semantic segmentation on captured images. From segmented images a point-extraction algorithm is applied in order to get the reference positions (set points) for the proposed controller. With this methodology, trajectory localization is feasible in less than 150 milliseconds with a root-meansquared- error (RMSE) of 6.99 pixels, using a U-Net neural network trained with 4200 crop field images. Meanwhile, with the visual servoing control algorithm it is possible to reach a settling time of around 12 seconds, being stable against robot slippage and image processing defects. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).