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Doctoral Thesis
DOI
10.11606/T.3.2007.tde-15022008-103833
Document
Author
Full name
Sergio Ribeiro Augusto
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2007
Supervisor
Committee
Ferreira, Ademar (President)
Del Moral Hernandez, Emilio
Gudwin, Ricardo Ribeiro
Sales, Roberto Moura
Yoneyama, Takashi
Title in Portuguese
Uma plataforma móvel para estudos de autonomia.
Keywords in Portuguese
Aprendizagem supervisionada
Arquitetura de robótica móvel
Autonomia
Redes de função de base radial
Tele-operação
Abstract in Portuguese
Neste trabalho é proposta uma plataforma robótica móvel, concebida de maneira modular e hierárquica, visando o estudo de diversos aspectos aplicados à navegação, tanto autônoma quanto semi-autônoma, em ambientes internos. O sistema proposto possibilita a implementação de arquiteturas reativas e híbridas com aprendizagem, sendo a importância e limitações desta última discutidas. Utilizando a plataforma desenvolvida, uma aplicação de navegação robótica com aprendizagem supervisionada é realizada, usando sensores de ultra-som e através de tele-operação. O objetivo é fazer com que o agente associe, em tempo real, suas próprias respostas sensoriais com as ações motoras realizadas pelo tele-operador, permitindo que a tarefa seja repetida autonomamente com alguma generalização. Para realizar tal mapeamento, uma rede de função de base radial (RBF), usando um algoritmo de aprendizado seqüencial, é apresentada e utilizada.
Title in English
A móbile platform for autonomy studies.
Keywords in English
Autonomy
Mobile robotic architecture
Radial basis function network
Supervised learning
Teleoperation
Abstract in English
This work presents a mobile robotic platform, built as a modular and hierarchical approach, aiming at the study of several aspects of indoor navigation. The proposed system allows the implementation of reactive and hybrid architectures with learning, for autonomous or semi-autonomous navigation. The importance and limitations of the learning characteristics are discussed. An application of robotic navigation with supervised learning is implemented using ultrasonic sensors and teleoperation. The aim is the agent to associate, in real time, its own sensorial perception to the motor actions realized by a teleoperator, allowing the task to be repeated in an autonomous way, with some generalization. To make the corresponding mapping, a radial basis function network (RBF), trained by a sequential learning algorithm, is presented and used.
 
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Publishing Date
2008-03-03
 
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