Density-Invariant Registration of Multiple Scans for Aircraft Measurement

In the aviation industry, the demand for high accuracy airplane product is growing, which makes precise production of airplane parts and accurate manufacturing increasingly important. To this end, it is crucial to be able to accurately measure the whole surface of an aircraft. 3-D laser scanner is widely utilized to capture the local shapes, represented as 3-D point clouds, of an object from different viewpoints. Multiview registration of point clouds is therefore a critical step to obtain the whole shape of an object. In this article, we propose a global registration framework to simultaneously align multiple point clouds with target detection and hierarchical optimization for aircraft inspection. By placing some targets (i.e., markers) surrounding an aircraft, we first scan the aircraft by putting a laser scanner around the aircraft at various stations, resulting in a number of laser scans which contain the point clouds of aircraft parts as well as targets. By detecting the centers of targets automatically, all partial point clouds are initially aligned to the global coordinate system. Furthermore, we tackle the influence of nonuniform distribution of point cloud density on registration accuracy, which has not been extensively studied so far, due to the large size of the aircraft. Existing approaches cannot directly apply to large size point clouds’ registration due to the aforementioned challenge. To address this issue, we propose a density-invariant area-based method to measure the overlapped region. On this basis, a hierarchical optimization registration method is used to achieve multiview registration of aircraft point clouds, and thereby the entire geometry shape of the aircraft is accurately obtained. A variety of experiments on real raw data demonstrate the effectiveness and robustness of our proposed framework.

I. Introduction

In aircraft manufacturing industry, aircraft assembly accuracy inspection is an important process of the final assembly line, such as aircraft defect inspection [1], skin surface inspection [2], [3], and surface deformation inspection [4]. Since it significantly affects the final aerodynamic shape, evaluation of the error in the final assembly and verifying its conformity is critical in the aircraft manufacturing process. The most common practice in the traditional aviation industry is to use the coordinate measuring machine (CMM). With its good measurement accuracy and versatility, it is widely used in the processing and inspection of small aviation components. In addition, the CMM can realize the automatic measurement of parts through the CMM program interface. For the large size aircraft components’ measurement, the section inspection method is adopted, where measurement is made on the surface of several parallel cross section on the object to be measured, and then compared with the design data. However, the individual key points of sections cannot reflect the overall shape of the aircraft. Besides, the inspection results are sensitive to measurement point density. Moreover, the use of traditional CMM is strongly limited by its reachability. For large-scale aircraft, it is impossible to move the CMM to the measured region. Hence, no in situ aircraft measurement can be implemented and the measurement must be always performed in the CMM platform, which is usually the inevitable exclusion element for most large-scale aircraft measurements. Consequently, contact measurement is inefficient and infeasible in aircraft measurement.