| 直线簇约束下的地面LiDAR点云配准方法 |
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| 引用本文： | 盛庆红,张斌,肖晖,陈姝文,王青,柳建峰. 直线簇约束下的地面LiDAR点云配准方法[J]. 武汉大学学报(信息科学版), 2018, 43(3): 406-412. DOI: 10.13203/j.whugis20150292 |
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| 作者姓名： | 盛庆红 张斌 肖晖 陈姝文 王青 柳建峰 |
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| 作者单位： | 1.南京航空航天大学航天学院, 江苏 南京, 210001 |
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| 基金项目： | 国家自然科学基金41101441国家自然科学基金41471381南京航空航天大学研究生创新基地（实验室）开放基金kfjj20161504江苏省普通高校研究生实践创新计划SJZZ15_0045 |
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| 摘 要： | 高精度的地面LiDAR点云配准是空间目标三维表面拓扑重建的关键，针对待配准LiDAR点云和基准LiDAR点云存在位置、姿态和比例缩放差异的问题，提出了基于直线簇的地面LiDAR点云配准方法。首先，根据直线间相交、平行和异面的拓扑关系，分别对待配准和基准LiDAR点云的直线进行聚簇，构建直线簇；然后，分别将同名直线用Plücker坐标表示，通过待配准LiDAR点云的直线簇在空间中的螺旋缩放运动，使其与基准LiDAR点云的直线簇比例尺一致，且同名Plücker直线重合，构建基于直线簇的共线条件方程，实现了比例因子和相对位姿一体化解算。实验结果表明，直线簇的螺旋缩放增强了配准方程的几何约束性，提高了抗噪声能力，实现了高精度的地面LiDAR点云配准。
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| 关 键 词： | LiDAR 点云配准 直线簇 Plücker坐标 螺旋运动 |
| 收稿时间： | 2016-02-21 |
A Registration Method Based on Line Cluster for Terrestrial LiDAR Point Clouds |
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| Affiliation: | 1.College of Astronautics, Nanjing University of Astronautics and Aeronautics, Nanjing 210001, China2.School of Environmental Science, Nanjing Xiaozhuang University, Nanjing 211171, China |
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| Abstract: | The high precision terrestrial LiDAR point clouds registration is the key to ensure 3D topological reconstruction of spatial objects. The reference LiDAR point clouds and the LiDAR point clouds to be registered have the issue of different position, attitude and scale. A registration method based on line cluster is proposed. Firstly, line cluster of the reference LiDAR point clouds and the LiDAR point clouds to be registered is respectively established according to the topological relation of lines. Then conjugate lines of point clouds are represented in Plücke coordinate. Through the spiral zooming motion of line cluster of the LiDAR point clouds to be registered, finally the scale of the two LiDAR point clouds is the same and the conjugate Plücke lines coincide with each other. The collinearity equations based on line cluster can solve the scale factor and the relative position and attitude simultaneously with high precision. The experimental results show that, the spiral and scaling of the line cluster enhances the geometric constraints of the registration equation, improves the ability of anti-noise, and realizes the high precision of terrestrial LiDAR point clouds registration. |
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