Abstract
The registration of long-strip, terrestrial laser scanning (TLS) point clouds is a prerequisite for various engineering tasks, including tunnels, bridges, and roads. An artificial target-based registration method is proposed in this paper to automatically calculate registration parameters (i.e., rotation, translation) of scanned pairs without initial estimations. The approach is based on the well-known Random Sample Consensus (RANSAC) method and effectively searches the point cloud for corresponding returns from a system of artificial targets. In addition, Closed Constraint Adjustment (CCA) is integrated into the registration method to significantly reduce the accumulative error. Experimental results demonstrate the robustness and feasibility of the proposed approach. It is a promising approach to register automatically long strips with limited external control points with satisfactory precision.
Highlights
The strong urbanization trends of the past few decades are leading to even more complex construction environments, raising the demand for dense and accurate three-dimensional (3D)data
In order to improve the overall accuracy, we propose a Random Sample Consensus (RANSAC)-based registration that is enhanced through a Closed Constraint Adjustment (CCA)
The terrestrial laser scanning (TLS) data facilitate the measurements of railway bridge piers in two aspects
Summary
The strong urbanization trends of the past few decades are leading to even more complex construction environments, raising the demand for dense and accurate three-dimensional (3D)data. The strong urbanization trends of the past few decades are leading to even more complex construction environments, raising the demand for dense and accurate three-dimensional (3D). The substantial air pollution problems encountered in the world’s megacities [1]. Force countries like China to consider alternative solutions to automobile-based transportation. High-speed rail is becoming a very attractive option, especially when considered against a backdrop of worsening airport congestion and given its reduced carbon footprint. In order to pursue this option we are faced with substantial engineering challenges. Viewed as are complex, challenging, and labor-intensive for traditional surveying solutions (e.g., leveling or triangulation). It is becoming even more challenging if one considers the need to regularly monitor these complex structures
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