Point cloud and BIM model registration based on genetic algorithm and ICP algorithm

With the rapid development of the construction industry, BIM technology, and 3D laser scanning technology are being used more and more widely, and there are many applications of combining BIM technology with 3D laser scanning technology, such as quality inspection, progress inspection, or digital preservation of ancient buildings. Therefore, this paper proposes a 3D point cloud and BIM model registration scheme based on genetic algorithm and ICP algorithm, firstly, the point cloud data is pre-processed by statistical denoising method for denoising and downsampling, and the BIM model data is converted to format data; then the coarse registration is performed by genetic algorithm, and the accurate registration is performed by ICP algorithm based on KD-tree, and finally, we experimentally verify the feasibility of the algorithm in this paper, and compared with the ICP algorithm, the registration efficiency and accuracy of the algorithm in this paper are greatly improved.

3D Laser Triangulation and Deep Learning Approach to Tunnel Inspection

Regular inspection of tunnel surfaces is an important practice from both a safety and tunnel asset management perspective. However, inspection for cracking and spalling is still predominantly a manual task, which is time consuming, subjective, and exposes on-foot staff to risk. This presentation will explore the use of 3D laser scanning technology and artificial intelligence to automate the inspection process with a Canadian metro case study being presented.

A novel method for approximating local changes in the surface absorption for laser marking using 3D laser scanning

Laser marking is a non-contact technique, which achieves colouring by using a laser beam to increase surface oxidation. Controlling the amount of heat induced into the part is essential in ensuring the desired degree of oxidisation. However, the induced heat is not only dependent on the process parameters, but also on the surface absorption, which in turn is dependent on the material, laser wavelength, and surface quality, i.e., current degree of oxidation and contaminants as well as surface roughness. This paper proposes a method for correlating backscatter from a 3D laser scanner with the surface absorption of sheet metal parts. The purpose is to determine local changes in the surface absorption caused by surface oxidation and contamination. The method utilises a 3D laser scanner, which projects a laser line at the surface and measures the resulting backscatter at an angle. The proposed solution applies a bi-directional reflectance model to reduce the influence of varying scanning angles. The method’s sensitivity to variations in surface treatments is investigated and validated against backscatter spectroscopy measurements. The results show that the proposed method can identify changes in the absorption. However, these were, in some cases, more than 70% higher compared to spectroscopy measurements.

A Post-Scan Point Cloud Colorization Method for Cultural Heritage Documentation

The 3D laser scanning technique is important for cultural heritage documentation. The laser itself normally does not carry any color information, so it usually requires an embedded camera system to colorize the point cloud. However, when the embedded camera system fails to perform properly under some external interferences, a post-scan colorization method is always desired to improve the point cloud visuality. This paper presents a simple but efficient point cloud colorization method based on a point-to-pixel orthogonal projection under an assumption that the orthogonal and perspective projections can produce similar effects for a planar feature as long as the target-to-camera distance is relatively short (within several meters). This assumption was verified by a simulation experiment, and the results show that only approximately 5% of colorization error was found at a target-to-camera distance of 3 m. The method was further verified with two real datasets collected for the cultural heritage documentation. The results showed that the visuality of the point clouds for two giant historical buildings had been greatly improved after applying the proposed method.