Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2304
Título: Configuration space synthesis for robotic manipulators using neural networks
Autor: Pashkevich, A.
Ruano, A. E.
Kazheunikau, M.
Palavras-chave: Robotic manipulators
Configuration space
Neural network
Learning algorithms
Off-line programming
Radial base function network
Data: 2002
Citação: Pashkevich, A.; Ruano, A. E.; Kazheunikau, M. Configuration Space Synthesis for Robotic Manipulators using Neural Networks, Trabalho apresentado em 5th Portuguese Conference on Automatic Control (Controlo 2002), In 5th Portuguese Conference on Automatic Control (Controlo 2002), Aveiro, 2002.
Resumo: The paper deals with configuration space syntheses for industrial robotic manipulators. A new efficient method is proposed that is based on a neural network collision model. To generate the collision model, a modification of the Radial Basis Function Network (RBFN) is used, which is trained applying the developed algorithm. An obstacle transformation algorithm that is based on conjugate vector model of a robotic cell is proposed. The method has been successfully applied to the design of a robotic manufacturing cell for the automotive industry.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2304
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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