Revista ELECTRO
Vol. 46 – Año 2024
Artículo
TÍTULO
Surveillance Two-Wheel Mobile Robot for People and Obstacle Detection in Restricted Areas
AUTORES
Vega-Luna, J.I.; Cosme-Aceves, J.F.; Salgado-Guzmán, G.; Sánchez-Rangel, F.J.; Tapia-Vargas, V.N.; Rodríguez-Tapia, V.G.; Andrade-González, E.A.
RESUMEN
Se presenta el desarrollo de un robot que sigue una línea, marcada en el perímetro de un laboratorio, cuyo objetivo fue que, al encontrar un obstáculo en el recorrido, capture la imagen frontal, marque en ella el objeto detectado y la envíe a una plataform a de Internet de las Cosas, así como al teléfono móvil del responsable del laboratorio. El funcionamiento del robot está controlado por un sistema embebido Raspberry Pi 5. Cuenta con un sistema de sensores infrarrojos que le permiten seguir la línea y un s ensor ultrasónico a través del cual determina la distancia al obstáculo. Incorpora una cámara de vídeo de 12.3 megapíxeles y un puente H para controlar los motores de las ruedas. La programación se realizó en Python con la biblioteca OpenCV. Las pruebas realizadas demostraron que el robot tiene una precisión del 9 8.4% en la detección de objetos y personas.
Palabras Clave: Cámara de video, Internet de las Cosas, OpenCV, Python, Raspberry Pi, robot
ABSTRACT
This study presents the development of a robot that follows a line, marked on the perimeter of a laboratory, whose objective was that, when encountering an obstacle on the route, it captures the frontal image, marks the detected object on it and sends it to an Internet of Things platform, as well as th e mobile phone of the person in charge of the laboratory. The operation of the robot is controlled by a Raspberry Pi 5 embedded system. It has a system of infrared sensors that allow it to follow the line and an ultrasonic sensor through which it determine s the distance to the obstacle. It incorporates a 12.3-megapixel video camera and an H-bridge to control the wheel motors. Programming was done in Python with OpenCV library. The tests carried out showed that the robot has an accuracy of 9 8,4% in detecting objects and people.
Keywords: Internet of Things, OpenCV, Python, Raspberry Pi, robot, video camera
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CITAR COMO:
Vega-Luna, J.I.; Cosme-Aceves, J.F.; Salgado-Guzmán, G.; Sánchez-Rangel, F.J.; Tapia-Vargas, V.N.; Rodríguez-Tapia, V.G.; Andrade-González, E.A., "Surveillance Two-Wheel Mobile Robot for People and Obstacle Detection in Restricted Areas", Revista ELECTRO, Vol. 46, 2024, pp. 374-380.
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