Applied Sciences (Nov 2024)

Multi-Platform Point Cloud Registration Method Based on the Coarse-To-Fine Strategy for an Underground Mine

  • Wenxiao Sun,
  • Xinlu Qu,
  • Jian Wang,
  • Fengxiang Jin,
  • Zhiyuan Li

DOI
https://doi.org/10.3390/app142210620
Journal volume & issue
Vol. 14, no. 22
p. 10620

Abstract

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Spatially referenced and geometrically accurate laser scanning is essential for the safety monitoring of an underground mine. However, the spatial inconsistency of point clouds collected by heterogeneous platforms presents challenges in achieving seamless fusion. In our study, the terrestrial and handheld laser scanning (TLS and HLS) point cloud registration method based on the coarse-to-fine strategy is proposed. Firstly, the point features (e.g., target spheres) are extracted from TLS and HLS point clouds to provide the coarse transform parameters. Then, the fine registration algorithm based on identical area extraction and improved 3D normal distribution transform (3D-NDT) is adopted, which achieves the datum unification of the TLS and HLS point cloud. Finally, the roughness is calculated to downsample the fusion point cloud. The proposed method has been successfully tested on two cases (simulated and real coal mine point cloud). Experimental results showed that the registration accuracy of the TLS and HLS point cloud is 4.3 cm for the simulated mine, which demonstrates the method can capture accurate and complete spatial information about underground mines.

Keywords