A Road Following Approach Using Artificial Neural Networks Combinations


Autoria(s): SHINZATO, Patrick Yuri; WOLF, Denis Fernando
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2011

Resumo

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CNPq

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

FAPESP[573963/2008-9]

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

FAPESP[08/57870-9]

Identificador

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, v.62, n.3/Abr, p.527-546, 2011

0921-0296

http://producao.usp.br/handle/BDPI/28986

10.1007/s10846-010-9463-2

http://dx.doi.org/10.1007/s10846-010-9463-2

Idioma(s)

eng

Publicador

SPRINGER

Relação

Journal of Intelligent & Robotic Systems

Direitos

restrictedAccess

Copyright SPRINGER

Palavras-Chave #Image processing #Navigation #Machine learning #MATHEMATICAL-THEORY #COMMUNICATION #Computer Science, Artificial Intelligence #Robotics
Tipo

article

original article

publishedVersion