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<p>The initial position difference of the mine hoist skip point cloud image acquired by the depth camera is large, and the overlap area is small, so the traditional alignment algorithm suffers from the problems of long alignment time and poor accuracy, which cannot meet the demand of real time and accurate monitoring. Based on the traditional alignment algorithm, this paper introduces the coordinate system reset algorithm and proposes an improved multi-step composite alignment algorithm, which can quickly align the skip point cloud and synthesize a complete skip point cloud model. Based on the constructed mine hoist skip visual monitoring system, a skip point cloud alignment experiment is carried out. The experimental results show that compared with the traditional alignment algorithm without preprocessing, the improved algorithm proposed in this paper can improve the alignment accuracy by about 5% and reduce the alignment time by about 20.95%, and the more the number of point clouds involved in the calculation, the more obvious the improvement effect is. The accuracy and real-time performance of the proposed algorithm provide guidance for the application of non-contact visual monitoring in the field of coal mines.</p>

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Research on rapid registration of mine hoist skip based on multi-step composite registration

  • 期刊论文

  • 发表日期：

    2025年8月8日

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  • Yangyang Guo,
  • Zuzhi Tian,
  • Minjian Zhu,
  • Zezheng Wang,
  • Zhiyuan Shi,
  • Xiangfan Wu,
  • Fangwei Xie

摘要

The initial position difference of the mine hoist skip point cloud image acquired by the depth camera is large, and the overlap area is small, so the traditional alignment algorithm suffers from the problems of long alignment time and poor accuracy, which cannot meet the demand of real time and accurate monitoring. Based on the traditional alignment algorithm, this paper introduces the coordinate system reset algorithm and proposes an improved multi-step composite alignment algorithm, which can quickly align the skip point cloud and synthesize a complete skip point cloud model. Based on the constructed mine hoist skip visual monitoring system, a skip point cloud alignment experiment is carried out. The experimental results show that compared with the traditional alignment algorithm without preprocessing, the improved algorithm proposed in this paper can improve the alignment accuracy by about 5% and reduce the alignment time by about 20.95%, and the more the number of point clouds involved in the calculation, the more obvious the improvement effect is. The accuracy and real-time performance of the proposed algorithm provide guidance for the application of non-contact visual monitoring in the field of coal mines.