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Robot vision with cellular neural networks: A practical implementation of new algorithms

  • Giovanni Egidio Pazienza*
  • , Xavier Ponce-García
  • , Marco Balsi
  • , Xavier Vilasís-Cardona
  • *Corresponding author for this work

Research output: Indexed journal article Articlepeer-review

18 Citations (Scopus)

Abstract

Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermore, we show the implementation of an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a digital signal processor (DSP). We successfully tested the two algorithms on this robot.

Original languageEnglish
Pages (from-to)449-462
Number of pages14
JournalInternational Journal of Circuit Theory and Applications
Volume35
Issue number4
DOIs
Publication statusPublished - Jul 2007

Keywords

  • Artificial vision
  • Autonomous robot
  • CNN
  • Obstacle avoidance
  • Tracking

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