Cart (Loading....) | Create Account
Close category search window
 

Path planning in a 2-D known space using neural networks and skeletonization

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

5 Author(s)
Bourbakis, N.G. ; Sch. of Nucl. Eng., Purdue Univ., West Lafayette, IN, USA ; Goldman, D. ; Fematt, R. ; Vlachavas, I.
more authors

A neural network and a skeletonization based path planning in a 2D known space is presented. For the neural network path planning approach a Kohonen self-organizing net has been chosen, while for the skeletonization Kwok's method (1988) was used. The output of the network represents a reduced representation of the free space available for robotic movement in a 2D known environment

Published in:

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on  (Volume:3 )

Date of Conference:

12-15 Oct 1997

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.