Control System of the RobotManipulator with Use of Neural Network Algorithms of Restriction of Work Area of the Gripper

I. V. Voynov, A. M. Kazantsev, B. A. Morozov, M. V. Nosikov

Abstract


This article covers control system architecture of industrial robot (manipulator), designed to work in heavy nuclear fields. To increase safety of manipulator control and moving an additional level of monitoring gripper position has been added to control system. This level includes artificial neural network, based on perceptron with output signal in range [0;1], which is used as a coefficient of transferring manual controls from joysticks to internal loops of control system. Outlined the way of preparing teaching data set for neural network and results of control system math modeling.


Keywords


robot-manipulator; artificial neural network; perceptron; training set; control system

References


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Назаров, А.В. Нейросетевые алгоритмы прогнозированиия и оптимизации систем / А.В. Назаров, А.И. Лоскутов. – СПб.: Наука и техника, 2003. – 384 с.

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DOI: http://dx.doi.org/10.14529/ctcr170404

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