An experimental study on evolutionary reactive behaviors for mobile robots navigation

Mobile robot's navigation and obstacle avoidance in an unknown and static environment is analyzed in this paper. From the guidance of position sensors, artificial neural network (ANN) based controllers settle the desired trajectory between current and a target point. Evolutionary algorithms wer...

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Autores principales: Fernández León, José A., Tosini, Marcelo Alejandro, Acosta, Gerardo, Acosta, Nelson
Formato: Articulo
Lenguaje:Inglés
Publicado: 2005
Materias:
Ciencias Informáticas
Robotics
Neural nets
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9591
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec05-4.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9591
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Robotics
Neural nets
spellingShingle Ciencias Informáticas
Robotics
Neural nets
Fernández León, José A.
Tosini, Marcelo Alejandro
Acosta, Gerardo
Acosta, Nelson
An experimental study on evolutionary reactive behaviors for mobile robots navigation
topic_facet Ciencias Informáticas
Robotics
Neural nets
description Mobile robot's navigation and obstacle avoidance in an unknown and static environment is analyzed in this paper. From the guidance of position sensors, artificial neural network (ANN) based controllers settle the desired trajectory between current and a target point. Evolutionary algorithms were used to choose the best controller. This approach, known as Evolutionary Robotics (ER), commonly resorts to very simple ANN architectures. Although they include temporal processing, most of them do not consider the learned experience in the controller's evolution. Thus, the ER research presented in this article, focuses on the specification and testing of the ANN based controllers implemented when genetic mutations are performed from one generation to another. Discrete-Time Recurrent Neural Networks based controllers were tested, with two variants: plastic neural networks (PNN) and standard feedforward (FFNN) networks. Also the way in which evolution was performed was also analyzed. As a result, controlled mutation do not exhibit major advantages against over the non controlled one, showing that diversity is more powerful than controlled adaptation.
format Articulo
Articulo
author Fernández León, José A.
Tosini, Marcelo Alejandro
Acosta, Gerardo
Acosta, Nelson
author_facet Fernández León, José A.
Tosini, Marcelo Alejandro
Acosta, Gerardo
Acosta, Nelson
author_sort Fernández León, José A.
title An experimental study on evolutionary reactive behaviors for mobile robots navigation
title_short An experimental study on evolutionary reactive behaviors for mobile robots navigation
title_full An experimental study on evolutionary reactive behaviors for mobile robots navigation
title_fullStr An experimental study on evolutionary reactive behaviors for mobile robots navigation
title_full_unstemmed An experimental study on evolutionary reactive behaviors for mobile robots navigation
title_sort experimental study on evolutionary reactive behaviors for mobile robots navigation
publishDate 2005
url http://sedici.unlp.edu.ar/handle/10915/9591
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec05-4.pdf
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