Abstract
The use of vision systems for industrial robot guidance and quality control becomes much harder when the manufactured products and their components are small and possess reflective surface. To assure an effective automated visual inspection of such components, novel solutions are required, able to perform more advanced image analysis and tackle noise and uncertainty. This paper proposes a concept of multi-camera/multi-pose inspection station for star washers inspection, and presents the first results of a functional prototype implementation of it in a robotic cell. The processes of vision-guided part picking from a flexible feeder and close-range inspection in a dedicated rig are described. Solutions for the vision-based tasks of parts identification, machine learning-based classification, circular objects image analysis and star washer teeth segmentation are presented, and further directions are outlined.