WP1: Development and validation of D MTs of 3D scanning systems

The aim of this work package is to develop measurement models for use with D‑MTs of 3D scanning systems including instrumental, environmental and target influences on the measurement result. A modular approach will be followed to allow model refinement and adjustment to different measurement scenarios and different scanner configurations. The generated large point clouds of the models or D‑MTs will be in a format compatible with existing commercial 3D analysis software. The measurement uncertainty of the point clouds will be determined following the GUM (Guide to the Expression of Uncertainty in Measurement) and its supplements.

Task 1.1: Development of the D-MT backlog

Task 1.2: Development of generic instrument models (D-MTs) for TLS

Task 1.3: Development of a generic instrument model (D‑MT) for the NGMC‑LiDAR instrument

Task 1.4: Free‑space light propagation and light‑surface interaction

Task 1.5: D‑MT completion and verification

WP2: Quality of point clouds

The aim of this work package is to assess the quality of point clouds in dimensional metrology through comparisons using a variety of measurement standards with typical (i) dimensions, (ii) features and (iii) materials generated with 3D scanning systems and D‑MTs of those instruments. Based on these results and the measurement uncertainty, a metric will be determined for the metrological quality of the point cloud(s) generated by 3D scanning systems. The purpose of the metric is to indicate the point cloud quality with respect to the processing in the digital workflow. For the development of the metric, the point clouds generated from different types of scanners and their D‑MTs will be collected for various artefacts and systematically analysed.

Task 2.1: Development of a standardised measurement strategy

Task 2.2: Generation of representative point clouds

Task 2.3: Point cloud dataset evaluation, analysis and development of a quality metric

WP3: Robust reference generator of generic datasets for validating fusion/registration software

This work package aims to develop and establish reference datasets for the assessment and verification of software tools deriving geometric or radiometric features from point clouds. The reference datasets will be suitable for deriving the achievable measurement uncertainty (calculation error target <1 nm) and data fusion of multiple scans, will be part of the verification scenarios (where appropriate). Datasets will comprise (i) classical geometries such as spheres, planes, cylinders and (ii) more complex geometries that are typical for two or more applications from industrial metrology, aerospace and geodesy.

Task 3.1: Implementation and validation of a robust generator of reference data for evaluating registration and fusion software

Task 3.2: Generation of reference datasets for validating commercial and open‑source software for dense cloud point data registration and fusion

Task 3.3: Verification with respect to measurement application results

WP4: Implementing new concepts and tools for digital transformation in geometric metrology

The aim of this work package is to use the outcomes of WPs 1‑3, to (i) develop guidelines for the uncertainty assessment and object classification of the geometric and radiometric features that are derived from large coordinate point clouds, (ii) to determine the measurement uncertainty of target measurement features, using case studies from industrial metrology, aerospace, or geodesy and (iii) to design and establish novel calibration or verification services for scanning systems.

Task 4.1: Case study: SI traceability of 3D laser scans of large geodetic networks

Task 4.2: Case study: a rigorous metrology framework for cargo logistics

Task 4.3: Case study: laser scanning in the aerospace industry

Task 4.4: Novel calibration and verification service concepts for 3D scanning systems

Task 4.5: The uncertainty assessment of geometric point cloud products