Selecting Feasible Trajectories for Robot-Based X-ray Tomography by Varying Focus-Detector-Distance in Space Restricted Environments

Abstract

Computed tomography has evolved as an essential tool for non-destructive testing within the automotive industry. The application of robot-based computed tomography enables high-resolution CT inspections of components exceeding the dimensions accommodated by conventional systems. However, large-scale components, e.g. vehicle bodies, often exhibit trajectory-limiting elements. The utilization of conventional trajectories with constant Focus-Detector-Distances can lead to anisotropy in image data due to the inaccessibility of some angular directions. In this work, we introduce two approaches that are able to select suitable acquisitions point sets in scans of challenging to access regions through the integration of projections with varying Focus-Detector-Distances. The variable distances of the X-ray hardware enable the capability to navigate around collision structures, thus facilitating the scanning of absent angular directions. The initial approach incorporates collision-free viewpoints along a spherical trajectory, preserving the field of view by maintaining a constant ratio between the Focus-Object-Distance and the Object-Detector-Distance, while discreetly extending the Focus-Detector-Distance. The second methodology represents a more straightforward approach, enabling the scanning of angular sectors that were previously inaccessible on the conventional circular trajectory by circumventing the X-ray source around these collision elements. Both the qualitative and quantitative evaluations, contrasting classical trajectories characterized by constant Focus-Detector-Distances with the proposed techniques employing variable Focus-Detector-Distances, indicate that the developed methods improve the object structure interpretability for scans of limited accessibility.