Automatic registration method for multisensor datasets adopted for dimensional measurements on cutting tools

Abstract

Multisensor systems with optical 3D sensors are frequently employed to capture complete surface information by measuring workpieces from different views. During coarse and fine registration the resulting datasets are afterward transformed into one common coordinate system. Automatic fine registration methods are well established in dimensional metrology, whereas there is a deficit in automatic coarse registration methods. The advantage of a fully automatic registration procedure is twofold: it enables a fast and contact-free alignment and further a flexible application to datasets of any kind of optical 3D sensor. In this paper, an algorithm adapted for a robust automatic coarse registration is presented. The method was originally developed for the field of object reconstruction or localization. It is based on a segmentation of planes in the datasets to calculate the transformation parameters. The rotation is defined by the normals of three corresponding segmented planes of two overlapping datasets, while the translation is calculated via the intersection point of the segmented planes. First results have shown that the translation is strongly shape dependent: 3D data of objects with non-orthogonal planar flanks cannot be registered with the current method. In the novel supplement for the algorithm, the translation is additionally calculated via the distance between centroids of corresponding segmented planes, which results in more than one option for the transformation. A newly introduced measure considering the distance between the datasets after coarse registration evaluates the best possible transformation. Results of the robust automatic registration method are presented on the example of datasets taken from a cutting tool with a fringe-projection system and a focus-variation system. The successful application in dimensional metrology is proven with evaluations of shape parameters based on the registered datasets of a calibrated workpiece.

A Globe Calibration Method for Optical Multisensor in 3D Complex Surface Measurement System

“…is a known point on the plane, MSLS and MCHS are, respectively, the normalized homogeneous coordinates of M SLS and M CHS , H is a 3 × 4 matrix, and (11) gives the Euclidean distance between a laser point and the calibration plane. Given different poses of the calibration board, we defined an error function e as the sum of such distances for each CHS point j in the very estimated 3D plane i:…”

“…One adopts a unified calibration object according to the different types of sensors and realizes the global calibration by measuring the calibration object with each sensor [8][9][10]. The other adopts the numerical calculation of the rigid-body transformation matrix by extracting three-dimensional data characteristics of the same object measured by each sensor to achieve global calibration [11,12].…”

“…A common reference coordinate system was created adopting a multistep registration method to match the datasets of two inhomogeneous sensors. Shaw et al [11] adopted a two-step method that comprised coarse and fine registration with some features of the measured parts and then calculated the common reference coordinates automatically.…”

Metrological solutions for an adapted inspection of parts and tools of a sheet-bulk metal forming process

“…Thereby each feature is measured by a sensor with a feature adapted measurement range, resolution and uncertainty. The resulting several datasets are combined together, which leads to a holistic dataset of different scales [21]. The inspection principle is shown in Fig.…”

Qualification concept for optical multi-scale multi-sensor systems

“…Only if there is a large overlapping area with at least one significant feature can an automatic algorithm, e.g. presented in Shaw et al (2013), be considered, but often this requirement cannot be met. In contrast to this for the following fine registration, various automatic algorithms are available.…”