Robust vision-based joint tracking for laser welding of curved closed-square-butt joints

Robotized laser beam welding of closed-square-butt joints is sensitive to how the focused laser beam is positioned in relation to the joint, and existing joint tracking systems tend to fail in detecting the joint when the gap and misalignment between the work pieces are close to zero. A camera-based system is presented based on a high dynamic range camera operating with LED illumination at a specific wavelength and a matching optical filter. An image processing algorithm based on the Hough transform extracts the joint position from the camera images, and the joint position is then estimated using a Kalman filter. The filter handles situations, when the joint is not detectable in the image, e.g., when tack welds cover the joint. Surface scratches, which can be misinterpreted as being the joint, are handled by a joint curve prediction model based on known information about the nominal path defined by the robot program. The performance of the proposed system has been evaluated off line with image data obtained during several welding experiments.