FILAMENT EXTRACTION IN 3D PRINTING OF SHOTCRETE WALLS FROM TERRESTRIAL LASER SCANNER DATA

Abstract

This paper presents a method for filament extraction as a step in Shotcrete 3D printing (SC3DP) for quality control using Terrestrial Laser Scanning (TLS) after the printing process. The proposed approach involves comparing a Point Cloud (PC) generated from TLS data with the original design model using Cloud-to-Model (C2M) distance to obtain a coloured deviation map. This deviation map is then rasterized into an image with the same size as the object, with each pixel's colour representing the C2M distance. The method incorporates denoising techniques, such as bilateral filtering, and applies Canny edge detection to identify the filaments’ contour. Morphological operations are used to extract only the horizontal edges relevant to the planned printing path. To connect isolated edges, an algorithm based on the M-estimator sample consensus (MSAC) algorithm is employed to fit lines accurately. The proposed method achieves an average precision score of 76% in detecting printing filaments of a shotcrete wall. The results demonstrate a reliable quality control capability and the potential for early identification of manufacturing-related issues.