Iterative automatic global registration algorithm for multi-view point cloud of underground tunnel space

Abstract

Aiming at the narrow and long tunnel structure, few internal features, and a large amount of point cloud data, the existing registration algorithms and commercial software registration results are not ideal, an iterative global registration algorithm is proposed for massive underground tunnel point cloud registration, which is composed of local initial pose acquisition and global adjustment. Firstly, the feature point coordinates in the point cloud are extracted, and then the station-by-station registration is performed according to the Rodrigues matrix. Finally, the registration result is considered as the initial value of the parameter, and the global adjustment of all observations is carried out. The observation values are weighted by the selection weight iteration method and the weights are constantly modified in the iteration process until the threshold conditions are met and the iteration stops. In this paper, the experimental data, made up of 85 stations of point cloud data, are from the Xiamen subway tunnel, which is about 1300 m long. When the accumulated error of station-to-station registration is too large, several stations are regarded as partial wholes, and the optimal registration is achieved through multiple global adjustments, and the registration accuracy is within 5 mm. Experimental results confirm the feasibility and effectiveness of the algorithm, which provides a new method for point cloud registration of underground space tunnel.

Development of ground-based LIDAR measurement system based on BeiDou/GNSS positioning and 5G technologies

“…The embedded microcontroller decodes the time information into a timestamp and synchronizes the time information to the LIDAR and the high-precision motor using the self-developed time synchronization module [13][14] . Through the 5G module, the real-time scanning data is sent to the remote terminal, which receives the data and performs multi-frame registration of the point cloud through linear interpolation algorithm points, followed by coarse registration of the multi-station laser point cloud according to BeiDou/GNSS coordinates and fine registration using the Rodriguez matrix to complete the overall registration [15][16][17] . The aligned laser point cloud data are segmented and formatted to obtain the data format supported by the real-time point cloud management and visualization system and combined with the LOD scheduling strategy to realize the laser point cloud data visualization.…”

Optimized GICP registration algorithm based on principal component analysis for point cloud edge extraction

“…Common key point extraction is based on curvature change, 30 covariance matrix, 31 Gaussian difference, and scale space. 32 Such as Intrinsic Shape Signatur (ISS), 33 Normal Aligned Radial Feature (NARF), 34 Scale-invariant feature transform (SIFT), 35,36 3D Harris, 37 and other algorithms. However, the feature point algorithm with single information has some problems, such as low robustness, easy to be affected by noise, and large time complexity.…”

“…(2) Different from the monogeneity of feature point information in literature, [33][34][35][36][37] the algorithm determines feature contour points [50][51][52]…”

Low-cost fixed-angle ground-based lidar integration with point cloud registration

“…This lidar consists of devices such as lasers, scanners, photodetectors and navigators with complex structures, and its hardware cost is high and its stability is difficult to guarantee under long operation [7] [8] because the accurate high-frequency rotation of the instrument is achieved by a complex structure. A solid-state lidar was developed to address the drawbacks of mechanical lidars, which can operate continuously in harsh environments such as high and low temperatures, vibrations, and high humidity [9][10][11]. Compared with mechanical lidars, solid-state lidars only scan at a certain angle in one direction [12] [13], making its scanning range limited, but it does not have a complex structure similar to mechanical high-frequency rotation, and its size is significantly reduced and its durability is substantially improved [14][15] .…”