Trajectory Tracking Control of KUKA KR 6 R900-2 Robotic Arm for Welding Applications

Abstract

This study presents an analysis of precision control for the KUKA KR R900-2 robotic arm during welding operations along predefined circular and square paths, emphasizing the use of image processing for navigation. The research compares the performance of Proportional-Integral-Derivative (PID) and Model Reference Adaptive Control (MRAC) systems in maintaining welding accuracy, especially with complex geometries. By integrating SOLIDWORKS for design and MATLAB for image processing, the study demonstrates how combining computer-aided design with advanced image processing enhances the precision of robotic welding. Results indicate that the adaptive controller outperforms the PID controller, achieving a reduction in mean squared error by up to 75% and improving response times. This underscores the adaptive controller's potential to significantly enhance automated welding processes. The findings contribute valuable insights into utilizing sophisticated control systems to improve the efficiency and quality of robotic welding in advanced industrial applications.