CREATING COMPUTER SIMULATION OF MOVEMENT CONTROL PROCESSES OF ROBOT-MANIPULATORS

Abstract

This article presents a study of algorithms using technical vision to control a robotic arm. With the increasing number of robots used in industry and other industries, the need for reliable and accurate control algorithms has increased. Thus, the relevance of the topic increases, and research in this area can significantly improve the efficiency and safety of robotic systems.  The purpose of this article is a comprehensive study of various control algorithms, as well as the integration of technical vision into control systems.

Robot manipulator control algorithms are a set of mathematical procedures and methods that allow robots to perform certain movements and tasks with the required efficiency and accuracy. To do this, the robot receives important data about the world around it using technical vision. The article discusses three main types of algorithms: inverse kinematics, PID controllers, and machine learning algorithms. Inverse kinematics determines the angles of rotation of the joints of the robot, which are necessary to achieve a given position and orientation of the working tool. The PID controller controls the movements of the robot's joints. By controlling the speed and force, it corrects errors between the actual and set position. Using machine learning methods allows you to learn new tasks and adapt your behavior to changing conditions.

Within the framework of this study, the theoretical aspects of algorithms and technical vision will be considered. The research was carried out on the Optima 2 manipulator from ZARNITZA and in the Simulink and MATLAB software package.