Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision

Silva, Luciana L. [UNESP]; Tronco, Mario L. [UNESP]; Vian, Henrique A. [UNESP]; Souza, Rogeria C. G. [UNESP]; Porto, Arthur J. V.

Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision

Data

2008-01-01

Autores

Silva, Luciana L. [UNESP]

Tronco, Mario L. [UNESP]

Vian, Henrique A. [UNESP]

Souza, Rogeria C. G. [UNESP]

Porto, Arthur J. V.

Editor

Slovak Univ Tech Bratislava

Resumo

Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

Palavras-chave

omnivision, mapping system, hierarchical artificial neural network (RNAH), attributes vector, affine invariant pattern

Como citar

Proceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processing. Bratislava: Slovak Univ Tech Bratislava, p. 487-490, 2008.