Calibración ojo a mano de un brazo robótico industrial con cámaras 3D de luz estructurada

• Ignacio Diaz-Cano ^[1] ; Fernando M. Quintana ^[1] ; Pedro L. Galindo ^[1] ; Arturo Morgado-Estevez ^[1]
  1. [1] Universidad de Cádiz

     Universidad de Cádiz

     Cádiz, España

     
• Localización: Revista iberoamericana de automática e informática industrial ( RIAI ), ISSN-e 1697-7920, Vol. 19, Nº. 2, 2022, págs. 154-163
• Idioma: español
• Títulos paralelos:
  • Eye-to-hand calibration of an industrial robotic arm with structured light 3D cameras
• Enlaces
  • Texto completo
• Resumen
  • español

    La visión artificial está cobrando cada día más auge en el mundo de la robótica industrial, ya que es necesario realizar tareas cada vez más precisas y autónomas, por lo que se necesita un posicionamiento del robot más exacto. Para ello se precisa del apoyo de un sistema de visión que sea el que preste al robot precisión en su pose, calibrando dicho sistema con respecto al robot. Este trabajo presenta una metodología sencilla para abordar esta forma de calibración, llamada ojo a mano, empleando una cámara 3D de luz estructurada que obtiene la información del mundo real y un brazo robótico industrial de seis ejes. Esto permite utilizar el algoritmo RANSAC para la determinación de los planos, cuya intersección nos da las coordenadas de los puntos, lo que supone una reducción notable de los errores, ya que las coordenadas proceden de planos ajustados a miles de puntos, lo cual hace que el sistema sea más robusto y capaz de obtener una matriz de transformación de las coordenadas de la cámara a la base del robot, que le permitirá abordar cualquier tarea que precise con una precisión eficiente. Se ha realizado el análisis de errores resultante utilizando dos cámaras 3D diferentes: una básica (Kinect 360) y otra industrial (Zivid ONE+ M).

  • English

    Computer vision is gaining more and more importance in the world of industrial robotics, since it is necessary to carry out increasingly precise and autonomous tasks, which is why a more exact positioning of the robot is needed. This requires the support of a vision system that is the one that gives the robot precision in its pose, calibrating said system with respect to the robot. This work presents a simple methodology to approach this form of calibration, called hand-eye, using a structured light 3D camera that obtains information from the real world and a six-axis industrial robotic arm. The method uses the RANSAC algorithm for the determination of the planes, which represents a notable reduction in errors, since the coordinates of the points sought come from planes adjusted to thousands of points. This allows the system to always have the ability to obtain a transformation matrix from the coordinates of the camera to the base of the robot. In addition, the proposed method is ideal for making a precision comparison between cameras, due to its simplicity and speed of use. In this study, the resulting error analysis was performed using two dfferent 3D cameras: a basic one (Kinect 360) and an industrial one (Zivid ONE + M).

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