Publication: Control para navegación de robot por medio de visión artificial
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2017-06
Defense date
2017-07-13
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Abstract
En la actualidad, las nuevas tecnologías se están aplicando a la hora de mejorar la conducción de vehículos. Existe tecnología simple, como sensores y cámaras, que nos ayudan a aparcar, hasta los ya conocidos coches de conducción autónoma. Con estos nuevos sistemas de conducción se busca mayor confort y seguridad para el conductor y para los peatones.
El objetivo de este trabajo es el desarrollo de un sistema de conducción autónomo guiado por visión artificial. El sistema estará integrado por un robot con cámara y una parte software que, a partir de las imágenes obtenidas por la cámara, guiará a un robot entre las líneas de un carril bici (simulando un vehículo autónomo en la carretera).
El robot estará compuesto por con una cámara, un chasis con cuatro motores y sus respectivos controladores de motores, todo ello integrado en una Raspberry Pi. La Raspberry Pi soportará un software desarrollado en Python y realizado con la ayuda de las librerias OpenCV, creadas para el desarrollo de la visión artificial, que cuentan con un gran número de funciones que se adecúan al objetivo.
Una vez perfeccionado el proyecto y desarrollando esta tecnología lo suficiente, podría utilizarse en otro tipo de vehiculos de menor tamaño y potencia que un automóvil y en espacios menos abiertos que una carretera, como podrían ser sillas de ruedas motorizadas de personas que no tienen la capacidad para controlarla en la calle o en un hospital. Otra opción podria ser guiar vehículos de menor tamaño dentro de una empresa que transporten a sus trabajadores, transportar viajeros por un aeropuerto o incluso por un campus de una Universidad. Las posibilidades son muchas debido a su bajo coste y su gran rendimiento.
Nowadays, new technologies are been applied to improve vehicle driving. There are simple technologies, such as sensors and cameras, which help us to park, even the well-known self-driving vehicles. These new autonomous driving systems look for comfort and safety for the driver and pedestrians. The aim of the work is the development of a computer vision-guided autonomous driving system. It will be composed of a robot with camera and software wich will guided the robot between the bicycle lane lines from the frames supplied by the camera (like an autonomous vehicle on the road). The robot will be composed of a camera, a chassis, four DC motors and their respective motor drivers, all of it is supported by a Raspberry Pi with a Python software and the OpenCV library, wich is created for computer vision development. This library has many functions to achieve the aim. When this project has been improved and this technologies has been enoughly developed, it would be used in friendly environments with any type of less powerfull and smaller vehicle than a car, for example to guide a motorized wheelchair of disabled people in a hospital. Another option would be to move passengers at the airport or students in a university campus. There are so many possibilities due to its low cost and high perfomance.
Nowadays, new technologies are been applied to improve vehicle driving. There are simple technologies, such as sensors and cameras, which help us to park, even the well-known self-driving vehicles. These new autonomous driving systems look for comfort and safety for the driver and pedestrians. The aim of the work is the development of a computer vision-guided autonomous driving system. It will be composed of a robot with camera and software wich will guided the robot between the bicycle lane lines from the frames supplied by the camera (like an autonomous vehicle on the road). The robot will be composed of a camera, a chassis, four DC motors and their respective motor drivers, all of it is supported by a Raspberry Pi with a Python software and the OpenCV library, wich is created for computer vision development. This library has many functions to achieve the aim. When this project has been improved and this technologies has been enoughly developed, it would be used in friendly environments with any type of less powerfull and smaller vehicle than a car, for example to guide a motorized wheelchair of disabled people in a hospital. Another option would be to move passengers at the airport or students in a university campus. There are so many possibilities due to its low cost and high perfomance.
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Visión artificial, Tecnología automovilística, Conducción autónoma, Raspberry Pi