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Optimization methods for hyper-redundant robots’ inverse kinematics in biomedical applications

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Detalhes bibliográficos
Resumo:The present work describes and compares several approaches applied to compute the inverse kinematics of a ten degrees of freedom hyper-redundant robot. The proposed approaches are based on an exhaustive method and several erroroptimization algorithms. The algorithms’ performance was evaluated based on two criteria: computational processing time and final actuator positioning error. The results obtained show that for a small number of modules (less or equal to four), the exhaustive method provides the best problem solution: acceptable computational processing time as well as minimum error. However, for larger number of modules, the error-optimization approach has far better performance regarding the error to processing time ratio. The mentioned hyper-redundant robot was projected to be used in biomedical applications.
Autores principais:Espinoza, Mario Sáenz
Outros Autores:Pereira, Ana I.; Gonçalves, José
Assunto:Robotics Optimization
Ano:2012
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Instituto Politécnico de Bragança
Idioma:português
Origem:Biblioteca Digital do IPB
Descrição
Resumo:The present work describes and compares several approaches applied to compute the inverse kinematics of a ten degrees of freedom hyper-redundant robot. The proposed approaches are based on an exhaustive method and several erroroptimization algorithms. The algorithms’ performance was evaluated based on two criteria: computational processing time and final actuator positioning error. The results obtained show that for a small number of modules (less or equal to four), the exhaustive method provides the best problem solution: acceptable computational processing time as well as minimum error. However, for larger number of modules, the error-optimization approach has far better performance regarding the error to processing time ratio. The mentioned hyper-redundant robot was projected to be used in biomedical applications.