The paper deals with a neural network control for the gravity compensation of a parallel kinematics robot. The network has been designed in a simulation environment then it has been implemented in robot’s controller by using an FPGA device that is part of an embedded system. After the training phase, several experiments have been performed on the prototype manipulator and the related datasets have been collected and elaborated. In the end, a comparative analysis has shown the improved performance of the neural network controller with respect to the inverse dynamics one, mainly due to the well-known difficulties in deriving explicit models of friction and play in the join
Design and Experimentation of a Neural Network Controller for a Spherical Parallel Robot / Tina, D.; Carbonari, Luca; Callegari, Massimo. - ELETTRONICO. - 1:(2012), pp. 250-255. (Intervento presentato al convegno ICINCO 2012 - 9th International Conference on Informatics in Control, Automation and Robotics: ICINCO 2012 tenutosi a Rome, Italy nel July 28-31, 2012).
Design and Experimentation of a Neural Network Controller for a Spherical Parallel Robot
CARBONARI, LUCA;CALLEGARI, Massimo
2012-01-01
Abstract
The paper deals with a neural network control for the gravity compensation of a parallel kinematics robot. The network has been designed in a simulation environment then it has been implemented in robot’s controller by using an FPGA device that is part of an embedded system. After the training phase, several experiments have been performed on the prototype manipulator and the related datasets have been collected and elaborated. In the end, a comparative analysis has shown the improved performance of the neural network controller with respect to the inverse dynamics one, mainly due to the well-known difficulties in deriving explicit models of friction and play in the joinI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
