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Sensitivity analysis of a crawl gait multi-objective optimization system

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Detalhes bibliográficos
Resumo:This paper describes the analysis of a crawl gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. In order to optimize the crawl gait, a multiobjective problem, an optimization system based on NSGAII allows to find a set of non-dominated solutions that correspond to different motor solutions The experimental results highlight the effectiveness of this multi-objective approach.
Autores principais:Oliveira, Miguel
Outros Autores:Silva, Pedro; Santos, Cristina; Costa, L.
Assunto:Evolutionary robotics Multi-objective optimization Genetic Genetic algorithms
Ano:2013
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:This paper describes the analysis of a crawl gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. In order to optimize the crawl gait, a multiobjective problem, an optimization system based on NSGAII allows to find a set of non-dominated solutions that correspond to different motor solutions The experimental results highlight the effectiveness of this multi-objective approach.