Abstract
The paper describes an intelligent manufacturing control system, designed to optimise flat material cutting from visually inspected scenes. A vision processor reconstructs the 2D image of the material, moving on a linear conveyor, from a dual line scan camera. A number of image features are extracted to identify internal defects. A skeletonization algorithm produces the binary representation of the useful surface to be manufactured. The vision system generates the maximal number of user-defined patterns that optimally cover the useful surface. The vision pattern data is converted to path specification to command the pattern cutting trajectories for a SCARA robot.
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