中文摘要：

针对经典的基于同名点状特征匹配的LiDAR点云配准算法存在计算量大,点状特征提取精度低,以及基于七参数转换模型的LiDAR点云配准算法中方程线性化过程对配准精度影响较大的特点,提出了以线状特征作为LiDAR点云配准的基元,利用四元数法来表达旋转矩阵,进而形成线状特征约束下基于四元数描述的LiDAR点云配准方法,给出了线状特征约束下三维相似变换的相似性测度表达方法,推导并论证了以线状特征作为配准基元时同名线状特征需要满足的条件。根据四元数与旋转变换矩阵之间的对应关系,求解了基于四元数法的旋转矩阵,并根据旋转矩阵求解了平移及缩放系数。

英文摘要：

Considering the large amount of computation ~ low accuracy of extracted point- like features are the two main disadvantages of traditional point-to-point based registration methods which iS designed for LiDAR point cloud, and the accuracy of registration results is seriously decreased by the linearization procedure of traditional 7-parameter based transfor- mation approaches, a new registration approach is designed to overcome above disadvanta ges, which selects linear features as registration primitives, and uses quaternion to represent rotation matrix. Similarity measure of the linear-feature-constrained 3D transformation pro- cedure is presented, and the formulation of registration procedure is exactly deduced. Be- sides, the detailed procedure of how to calculate rotation, translation g〉 scale is also presen- ted. Experiments show that the presented approach is efficient ＆ effective. More important- ly, by using quaternion to represent rotation matrix, the new presented approach avoids the decrease of accuracy, meanwhile, due to the characteristic of quaternion, it also needs few calculation resources compared to traditional registration methods.