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Ingeniería Mecánica

versión On-line ISSN 1815-5944

Resumen

BUITRAGO-SALAZAR, Germán  y  RAMOS-SANDOVAL, Olga. Visual servo-control system using neural networks and filters based on CIELAB. Ingeniería Mecánica [online]. 2015, vol.18, n.2, pp.100-108. ISSN 1815-5944.

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*b components) 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).

Palabras clave : visual servo-control system; CIELAB; neural networks; image filtering.

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