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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 972304, 11 pages
Research Article

3D Maps Representation Using GNG

University Institute for Computing Research, University of Alicante, P.O. Box 99, 03080 Alicante, Spain

Received 6 March 2014; Accepted 24 July 2014; Published 27 August 2014

Academic Editor: Yi Chen

Copyright © 2014 Vicente Morell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.