A Road Following Approach Using Artificial Neural Networks Combinations
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2011
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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 |
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 |