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.
Highlights
Compared with other technologies, LIDAR (Light Detection and Ranging) technology has the advantage of not being effected of environmental conditions and can carry out accurate measurement even in a dark tunnel, which makes it a preferred means for data acquisition in underground tunnels.[1]
When using LiDAR technology to collect a tunnel with a large-span linear structure, it is usually scanned from different angles and positions, and obtains the complete tunnel point cloud through data registration, which is an essential step for subsequent point cloud processing and analysis.[4]
In view of the narrow and long tunnel structure, few internal features, and a large amount of point cloud data, an iterative global registration algorithm is proposed by using target ball which is not limited by any scanning angle
Summary
LIDAR (Light Detection and Ranging) technology has the advantage of not being effected of environmental conditions and can carry out accurate measurement even in a dark tunnel, which makes it a preferred means for data acquisition in underground tunnels.[1]. In view of the narrow and long tunnel structure, few internal features, and a large amount of point cloud data, an iterative global registration algorithm is proposed by using target ball which is not limited by any scanning angle. The center coordinates of the target ball are used as features point for registration, and the registration results are taken as the initial values for global adjustment. When more registration sites are involved, it is more likely to cause error accumulation,[27] and the accuracy of station-tostation registration will correspondingly become lower In this case, the global adjustment method is used to reduce the accumulative error, and all the spatial transformation parameters and the unknown points adjustment values are calculated. A similar conclusion can be drawn from the comparison, the proposed method has advantages of registration accuracy and registration time in processing massive tunnel point cloud data
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