This paper addresses the problem of mapping large surfaces with a moving sensor. In particular, it proposes image registration and mapping algorithms that enable to use in continuous motion sensors that need multiple shots to perform a measurement. These methods exploit the knowledge of the shape of the part to inspect in a both efficient and accurate fashion, thus allowing to obtain a measurement quality comparable to that of static measurements, while guaranteeing fast sensor motion and thus short scanning times. This work describes the application of these methods for the mapping of carbon fibre parts with an inspection robot equipped with a sensor estimating 3D carbon fibre orientation from multiple 2D images captured with different illumination. Experiments on carbon fibre preforms of complex 3D shape demonstrates that this system accurately reconstructs in real-time the 3D fibre orientations of the outer layer of carbon fibre parts. Accuracy assessments report small errors within the tolerances allowed by the automotive industry on flat and generic 3D surfaces. The inspection robot system presented in this paper has been demonstrated both as an in-line quality inspection robot for production of carbon fibre preforms and as a measurement device for improving the draping process in the prototyping of carbon fibre parts.
Read full abstract