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Decentralized control of cooperative robotics system using neural networks for the purpose of an object balancing flat plate tasks
Author(s)
Date Issued
February 1, 2020
Type
Article
Abstract
In this article, the manipulation to handle the object on a plate using neural networks, design of 1-DOF robot arm under cooperative control, will be explained. The robot's system specifies the object position and velocity, an assignment oriented components for cooperative control. The novelty of this experiment is that under the decentralized control, the robot estimates the position and speed of the object for control end-effector of robot arm using the camera to track position and speed of the object according to training and assigned collaborative tasks which differ from other experiments that use sensors. The experiment includes three robot manipulators which were capable balancing the objects on flat plate with dataset to training and control servo motor assigned to the corresponding position and the end-effector in decentralized to control robotics. Overall, neural network method can be a training scheme using a cooperative robotics in a decentralized control.
Citation
International Journal of Intelligent Engineering and Systems, 13(1), 259-270, 2020