WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 17, 2018
Control Scheme for SCARA by Recurrent Neural Network Using Simultaneous Perturbation
Authors: ,
Abstract: Robots are widely used in many fields. It is important to provide many different methodologies for robot control. This paper proposes a real time scheme for robots control and learning using recurrent neural network. We handle a problem to control a position and a trajectory of tip of a Selective Compliance Assembly Robot Arm(SCARA) robot. We adopt the simultaneous perturbation optimization method as a learning rule of the recurrent neural networks(RNNs). Then the RNNs have to learn an inverse dynamics of the SCARA robot. Position and trajectory control of a SCARA robot using RNN are considered. We could confirm that the RNNs can learn the inverse dynamics and work as a neuro-controller. We describe details of the control scheme. Some experimental results for these control using an actual SCARA robot are shown.
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Keywords: Robot control, Learning, Recurrent neural networks, Simultaneous perturbation, SCARA, Inverse dynamics, Real time control
Pages: 146-155
WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 17, 2018, Art. #16