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Updated: Jul 23, 2025

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A Cross-Source Point Cloud Registration Algorithm Based on Trigonometric Mutation Chaotic Harris Hawk Optimisation

Bingyu Ren1, Hao Zhao1, Shuyang Han1

  • 1State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
Summary

This study introduces a novel method for creating accurate 3D models in hydraulic engineering by fusing data from multiple sources. The enhanced approach improves 3D model accuracy and integrity for complex projects.

Keywords:
3D laser scanningHarris hawk optimisationUAV tilt photographypoint cloud registration

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Area of Science:

  • Engineering
  • Geomatics
  • Computer Science

Background:

  • High-precision 3D models are crucial for digitalizing hydraulic engineering projects.
  • Traditional 3D reconstruction methods using single technologies struggle to balance data acquisition speed, precision, and multi-angle texture details in complex environments.

Purpose of the Study:

  • To develop a robust cross-source point cloud registration method for improved 3D model reconstruction in hydraulic engineering.
  • To enhance the accuracy and integrity of fused 3D models by integrating multi-source data.

Main Methods:

  • A novel cross-source point cloud registration method combining trigonometric mutation chaotic Harris hawk optimization (TMCHHO) for coarse registration and iterative closest point (ICP) for fine registration.
  • TMCHHO utilizes piecewise linear chaotic maps for initial population diversity and trigonometric mutation to prevent local optima.
  • The proposed method was validated on the Lianghekou project.

Main Results:

  • The integrated TMCHHO-ICP method demonstrated superior performance in point cloud registration compared to single-technology approaches.
  • The resulting fused 3D model exhibited enhanced accuracy and integrity.
  • The method effectively addressed the limitations of traditional single-surveying techniques in complex environments.

Conclusions:

  • The proposed cross-source point cloud registration method significantly improves the accuracy and integrity of 3D models in hydraulic engineering.
  • This approach offers a comprehensive solution for utilizing multi-source data, overcoming the limitations of single-mapping systems.
  • The findings have practical implications for digitalizing and managing complex hydraulic engineering projects.