A robust autonomous mobile forklift pallet recognition

  • Authors:

  • Guang-zhao Cui;Lin-sha Lu;Zhen-dong He;Li-na Yao;Cun-xiang Yang;Bu-yi Huang;Zhi-hong Hu

  • Affiliations:

  • Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China;Henan Province Key Laboratory of Infonnation and Electrical Appliances, Zhengzhou University of Light Industry, China

  • Venue:
  • CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

A visual pallet recognition system based on the accurate color segmentation is proposed. The basic idea is to get the pallet color feature samples from the images in working environment before the autonomous mobile forklift works. Then the algorithms of morphological filtering, Sobel edge detection and Hough transform are used to get the pallet forking side. At last, according to two corners of the forking side, the pallet midpoint coordinates of the forking part and the direction of the forking side are calculated, which are the pose provided for the autonomous mobile forklift engagement. Experimental results show that the visual recognition system has good real-time and robustness.