Robot based 3D scanning and recognition of workpieces

Abstract: Quality inspection of a product is central of many manufacturing processes. While inspection on flat surfaces can be made fairly autonomous today, highly reflective free-form objects is problematic in many ways. This thesis is one part out of a two-part project investigating in an autonomous way to recognize, model, store relevant information and inspect these kind of work pieces. This part will focus on the recognition, modeling and database design. The system, established in this thesis will use a robotic manipulator, an industrial camera and the handheld 3-D scanner Exascanner. We present a methodology for preparing a work piece to be inspected autonomously and a simple implementation of the proposed methodology. The implementation recognizes workpieces with a support vector machine trained on histogram of oriented gradients features. These features are extracted from several pictures taken from different angles around the workpiece. The use of different angles are to make the classifier more versatile and robust to object being rotated or moved. If the workpeice is not recognized a spiral shaped dome path is created, scaled with the help of the pictures already taken. This shape helps ensuring a high quality scan of objects were there is no shape information to be used. The robotic manipulator is used to move the scanner along the path around the object, creating a surface profile of the object. This profile is built up of triangular facets of various size and needs to be processed before inspection of the surface can be made. A recursive splitting algorithm is used to make the facets as equilateral as possible and to make their size more suitable for the viewing range of the surface inspection camera. As a final step this information is stored in a database to be used later as support during inspection.