By Topic

Vision based algorithm for path planning of a mobile robot by using cellular neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Gavrilut, I. ; Dept. of Electron., Oradea Univ. ; Gacsadi, A. ; Grava, C. ; Tiponut, V.

The paper presents a new vision based algorithm for mobile robots path planning in an environment with obstacles. Cellular neural networks (CNNs) processing techniques are used here for real time motion planning to reach a fixed target. The CNN methods have been considered a solution for image processing in autonomous mobile robots guidance. The choice of CNNs for the visual processing is based on the possibility of their hardware implementation in large networks on a single VLSI chip (cellular neural networks -universal machine, CNN-UM (Roska and Chua, 1993 and Kim et al., 2002))

Published in:

Automation, Quality and Testing, Robotics, 2006 IEEE International Conference on  (Volume:2 )

Date of Conference:

25-28 May 2006