Industrial Robot Training in the Simulation Using the Machine Learning Agent
Karle Nutonen, Vladimir Kuts, Tauno Otto
Abstract
Continuous change in manufacturing requires robotization, requiring a skilled workforce with robotic skills. It is also important for a manufacturing company to be able to transform its production process quickly. But now it is a long and complex process. The paper presents the simulation of the movement of an industrial robot in a digital environment, to which implemented the inverse kinematics functionality and machine learning model have been applied. The use of machine learning reduces the time required to develop the process and the investment in finding the path of the robot. The results obtained in the application of Bio-ik inverse kinematics and machine learning have been observed and analyzed as a simulation in the created research.