Sistema de servocontrol visual empleando redes neuronales y filtros en el dominio de CIELAB//Visual servo-control system using neural networks and filters based on CIELAB

Authors

  • Germán Buitrago Salazar Universidad Militar Nueva Granada Facultad de Ing. en Mecatrónica, Grupo de Investigación GAV, Bogotá
  • Olga Ramos Sandoval Universidad Militar Nueva Granada Facultad de Ing. en Mecatrónica, Grupo de Investigación GAV, Bogotá

Abstract

En este trabajo se presentan los resultados de un sistema servocontrol visual de un brazo robótico de seis grados de libertad. Para esto, se utiliza una red neuronal de tipo feed forward, entrenada por back propagation, para determinar la distancia entre el brazo robótico y un objeto de referencia, que permite ubicarlo en un espacio de trabajo. Las entradas de la red corresponden a la información obtenida de las imágenes capturadas por el Kinect, utilizando un filtro que discrimina la posición de los elementos, en el espacio de color CIELAB (Commission Internationale de l'Eclairage L*a*b components). El resultado de esta investigación demostró que la distancia estimada por la red tiene un margen de error menor, que el algoritmo propuesto en otros trabajos. Igualmente, se probó que el sistema de procesamiento de imágenes es más robusto a ruidos digitales, en comparación con los sistemas que utilizan filtros en el dominio RGB (Red-Green-Blue).

Palabras claves: sistema de servocontrol visual, CIELAB, redes neuronales, filtrado de imágenes.
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Abstract

In this paper the results of visual servo-control system for a robotic arm with six degrees of freedom are presented. For this purpose, a feed fordward neural network, which was trained by back propagation, is used to determine the distance between the robot arm and a reference object and sitting the robot in the workspace. The inputs of neural network correspond to the information obtained from the images captured by the Kinect, using a filter that discriminates the position of the elements in the CIELAB (Commission Internationale de l'Eclairage L*a*bcomponents) color space. The result of this research showed that the estimated distance with the network has an errorless than the algorithm proposed in other works. Similarly, it was proved that the image processing system is more robust to digital noise, compared to systems using filters in RGB (Red-Green-Blue).

Key words: visual servo-control system, CIELAB, neural networks, image filtering

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How to Cite

1.
Buitrago Salazar G, Ramos Sandoval O. Sistema de servocontrol visual empleando redes neuronales y filtros en el dominio de CIELAB//Visual servo-control system using neural networks and filters based on CIELAB. Ing. Mec. [Internet]. 2015 May 1 [cited 2025 Sep. 13];18(2):100-8. Available from: https://ingenieriamecanica.cujae.edu.cu/index.php/revistaim/article/view/514

Issue

Vol. 18 No. 2 (2015): mayo-agosto

Section

Original article

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