测绘通报 ›› 2026, Vol. 0 ›› Issue (5): 179-184.doi: 10.13474/j.cnki.11-2246.2026.0529

• 测绘地理信息技术应用案例 • 上一篇    

融合手持SLAM激光与影像数据的室内自动三维建模技术

张世杰1, 苗培培1, 徐林杰2, 高云龙3, 彭芳媛4, 李纯南1, 孙鑫浩1   

  1. 1. 北京飞马航遥科技有限公司, 北京 100096;
    2. 自然资源部城市国土资源监测与仿真重点实验室, 广东 深圳 518034;
    3. 武汉大势智慧科技有限公司, 湖北 武汉 430223;
    4. 成都航空职业技术大学, 四川 成都 610100
  • 收稿日期:2025-12-15 发布日期:2026-06-09
  • 通讯作者: 苗培培。E-mail:490880314@qq.com
  • 作者简介:张世杰(1989—),男,主要从事无人机及手持激光扫描仪研究。E-mail:zhangsj@feimarobotics.com
  • 基金资助:
    自然资源部城市国土资源监测与仿真重点实验室开放基金(KF-2023-08-10)

Indoor automatic 3D modeling technology integrating handheld SLAM LiDAR and image data

ZHANG Shijie1, MIAO Peipei1, XU Linjie2, GAO Yunlong3, PENG Fangyuan4, LI Chunnan1, SUN Xinhao1   

  1. 1. Beijing Feima Hangyao Technology Co., Ltd., Beijing 100096, China;
    2. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China;
    3. Wuhan Daspatial Technology Co., Ltd., Wuhan 430223, China;
    4. Chengdu Aeronautic Polytechnic University, Chengdu 610100, China
  • Received:2025-12-15 Published:2026-06-09

摘要: [目的]针对室内三维建模对高精度空间结构与丰富纹理的双重需求,为破解单一数据源的局限性及传统配准算法效率低、适应性差的问题,本文提出了一种高效、稳健且自动化程度高的室内三维建模技术。[方法]采用集成相机的手持激光SLAM扫描仪,同步采集高精度点云与纹理影像;基于设备出厂检校参数获取初始POS数据,提出了一种结合几何约束与特征匹配的改进点云-影像配准算法,实现数据高精度融合;通过点云驱动的几何建模与优化后的纹理映射完成三维重建。[结果]试验结果表明,所建三维模型几何误差≤2 cm,纹理真实感强,全流程耗时58.5 min,显著优于传统人工建模方法。[结论]该技术实现了激光点云与影像数据的优势互补,降低了对影像光照条件的敏感度,提升了建模效率与自动化水平,为室内实景三维重建提供了一种可靠的技术方案。

关键词: 室内实景三维模型, 自动三维重建, 点云-影像配准, 手持激光SLAM, 融合建模

Abstract: [Purposes] To address the dual requirements of high-precision geometry and realistic textures for indoor 3D modeling,as well as the limitations of single data sources and the inefficiency of traditional registration methods,this paper proposes an efficient,robust,and highly automated indoor 3D modeling technology.[Methods] A handheld laser SLAM scanner integrated with a camera is used to simultaneously collect high-precision point clouds and texture images.Initial POS data are derived from factory calibration parameters.An improved point cloud-image registration algorithm combining geometric constraints and feature matching is proposed to achieve high-precision data fusion.Subsequently,3D reconstruction is accomplished through point-cloud-driven geometric modeling and optimized texture mapping.[Findings] Experimental results indicate that the geometric error of the 3D model is less than 2 cm,with realistic textures.The entire process takes 58.5 min,significantly outperforming traditional manual modeling methods.[Conclusions] This technology leverages the complementary strengths of LiDAR point clouds and image data,reduces sensitivity to lighting conditions,improves modeling efficiency and automation,and provides a reliable technical solution for indoor realistic 3D reconstruction.

Key words: indoor realistic 3D model, automatic 3D reconstruction, point cloud-image registration, handheld laser SLAM, fusion modeling

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