Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/346906
Type: Artigo
Title: Control structure for a car-like robot using artificial neural networks and genetic algorithms
Author: Flórez, Camilo Andrés Cáceres
Rosário, João Maurício
Amaya, Dario
Abstract: The idea of improving human’s life quality by making life more comfortable and easy is nowadays possible using current technologies and techniques to solve complex daily problems. The presented idea in this work proposes a control strategy for autonomous robotic systems, specifically car-like robots. The main objective of this work is the development of a reactive navigation controller by means of obstacles avoidance and position control to reach a desired position in an unknown environment. This research goal was achieved by the integration of potential fields and neuroevolution controllers. The neuro-evolutionary controller was designed using the (NEAT) algorithm “Neuroevolution of Augmented Topologies” and trained using a designed training environment. The methodology used allowed the vehicle to reach a certain level of autonomy, obtaining a stable controller that includes kinematic and dynamic considerations. The obtained results showed significant improvements compared to the comparison work
Subject: Algoritmos genéticos
Redes neurais (Computação)
Country: Reino Unido
Editor: Springer
Rights: Aberto
Identifier DOI: 10.1007/s00521-018-3514-1
Address: https://link.springer.com/article/10.1007/s00521-018-3514-1
Date Issue: 2018
Appears in Collections:FEM - Artigos e Outros Documentos

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