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Particle swarm optimization versus genetic algorithm in manipulator trajectory planning

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Detalhes bibliográficos
Resumo:The aim of this study is the reduction of the computational burden associated with the evolutionary optimization of manipulator trajectory planning. This paper proposes the use of a particle swarm optimization algorithm to generate trajectories for robotic planar manipulators, based on direct kinematics. The design objective is to minimize the ripple in the trajectory time evolution. Several redundant and hyperredundant manipulators are considered. The particle swarm optimization algorithm is compared with genetic algorithm in solving the manipulator trajectory planning problem. Preliminary simulation results are presented.
Autores principais:Pires, E. J. Solteiro
Outros Autores:Oliveira, P. B. Moura; Tenreiro Machado, J. A.; Cunha, J. Boaventura
Assunto:Particle Swarm Optimization Genetic Algorithms Robotics Trajectory Planning Optimization
Ano:2006
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico do Porto
Idioma:inglês
Origem:Repositório Científico do Instituto Politécnico do Porto
Descrição
Resumo:The aim of this study is the reduction of the computational burden associated with the evolutionary optimization of manipulator trajectory planning. This paper proposes the use of a particle swarm optimization algorithm to generate trajectories for robotic planar manipulators, based on direct kinematics. The design objective is to minimize the ripple in the trajectory time evolution. Several redundant and hyperredundant manipulators are considered. The particle swarm optimization algorithm is compared with genetic algorithm in solving the manipulator trajectory planning problem. Preliminary simulation results are presented.