View Planning for Robotic Inspection of Tolerances Through Visual Tracking of Manual Surface Finishing Operations

Abstract

This article presents an approach for determining suitable camera view poses for inspection of surface tolerances based on visual tracking of the tool movements performed by a skilled worker. Automated surface inspection of a workpiece adjusted by manual operations depends on manual programming of the inspecting robot, or a time-consuming exhaustive search over the entire surface. The proposed approach is based on the assumption that the tool movements of the skilled worker coincide with the most relevant regions of the underlying surface of the workpiece, namely the parts where a manual process has been performed. The affected region is detected with a visual tracking system, which measures the motion of the tool using a low-cost RGBD-camera, a particle filter, and a CAD model of the tool. The main contribution is a scheme for selecting relevant camera view poses for inspecting the affected region using a robot equipped with a high-accuracy RGBD-camera. A principal component analysis of the tracked tool paths allows for evaluating the view poses by the Hotelling’s T-squared distribution test in order to sort and select suitable camera view poses. The approach is implemented and tested for the case where a large ship propeller blade cast in NiAl bronze is to be inspected by a robot after manual adjustments of its surface.