<![CDATA[The robot manipulator is an example of the advancement in control technology in the current industrial era. Robots with 4 degrees of freedom (DoF) in their movements are often used to increase efficiency and reduce accident risks in the industry. However, in solving the inverse kinematics of the robot manipulator, there is a computational complexity problem in determining the joint angle values. Therefore, this study aims to solve the inverse kinematics problem using artificial neural networks on the Robot OpenMANIPULATOR-X. This research involves data collection through forward kinematics, designing an artificial neural network model by testing the number of hidden layers, neurons, and learning rate, and testing the points of the neural network model results on the robot in a real plant. Keywords—Robot Manipulator, Inverse Kinematics, Artificial Neural Network]]>
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