Fast and robust bore detection in range image data for industrial automation

Abstract

This work presents a fast and robust method to precisely segment and locate bore holes of 4 to 50mm diameter. The task is solved by a robot moving a compact triangulation scanning sensor to all sides of the object and scanning the bore holes. Exploiting the knowledge about the expected bore diameter and bore pose makes it possible to develop highly robust algorithms for an industrial application. Sparse data of the bore hole is sufficient to segment the bore independent of bore hole chamfer type using a robust normal vector fit and a classification based on the Gaussian image. A sequential algorithm to fit the bore cylinder makes it possible to calculate the bore pose in less than 1 second. Experiments demonstrate that 120 degrees of the bore hole surface are sufficient for robust localization within 0.3mm and 0.5 degrees even in the presence of ghost points and notches in the bore holes.