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Yutaka Maeda
Naoyuki Ishibashi

Author(s) and WSEAS

Yutaka Maeda
Naoyuki Ishibashi

WSEAS Transactions on Systems

Print ISSN: 1109-2777
E-ISSN: 2224-2678

Volume 17, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 17, 2018

Control Scheme for SCARA by Recurrent Neural Network Using Simultaneous Perturbation

AUTHORS: Yutaka Maeda, Naoyuki Ishibashi

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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

KEYWORDS: Robot control, Learning, Recurrent neural networks, Simultaneous perturbation, SCARA, Inverse dynamics, Real time control


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[12] Y. Maeda and M. Wakamura, Simultaneous Perturbation Learning Rule for Recurrent Neural Networks and Its FPGA Implementation, IEEE Trans. on Neural Networks, 16, 2005, pp.1664- 1672.

WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 17, 2018, Art. #16, pp. 146-155

Copyright © 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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