Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/15171
Título: | Multiobjective optimization of a quadruped robot locomotion using a genetic algorithm |
Autor(es): | Oliveira, Miguel Costa, L. Rocha, Ana Maria A. C. Santos, Cristina Ferreira, Manuel João Oliveira |
Data: | 2011 |
Editora: | Springer |
Revista: | Advances in Intelligent and Soft Computing |
Resumo(s): | In this work, it is described a gait multiobjective optimization system that allows to obtain fast but stable robot quadruped crawl gaits. We combine bioinspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). A motion architecture based on CPGs oscillators is used to model the locomotion of the robot dog and a GA is used to search parameterizations of the CPGs parameters which minimize the body vibration, maximize the velocity and maximize the wide stability margin. In this problem, there are several conflicting objectives that leads to a multiobjective formulation that is solved using the Weighted Tchebycheff scalarization method. Several experimental results show the effectiveness of this proposed approach. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/15171 |
ISBN: | 978-3-642-20504-0 |
ISSN: | 1867-5662 |
Versão da editora: | The original publication is available at www.springerlink.com |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | LES/ALG - Capítulos de livros |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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AMR_wsc15_Robot_2011_not_original.pdf | 99,99 kB | Adobe PDF | Ver/Abrir |