The Master’s thesis deals with the challenge of welding gap tracking in automated robotic welding. The tracking system is based on a laser profilometer, attached to the robot arm, which captures the profile of the welding surface, processes the captured image data and transmits path corrections to the robot controller in real time. In order to achieve required integration, specialized algorithms were developed to identify deviations of the welding gaps, calculate the necessary adjustments and communicate them to the robot for real-time correction of the movement path. The implemented system showed significant improvements in weld seam tracking, effectively compensating for offsets and distortion of the planned welding path. The results confirm the potential of the system to improve the accuracy and reliability of automated welding processes.
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