文献类型：会议论文

英文题名：Point Cloud Registration Algorithm Based on Combination of NDT and PLICP

作者：Wang Qingshan[1];Zhang Jun[2]

第一作者：Wang Qingshan

通讯作者：Wang, QS[1]

机构：[1]Beijing Union Univ, Beijing Key Lab Informat Serv, Beijing, Peoples R China;[2]Beijing Union Univ, Coll Robot, Beijing, Peoples R China

第一机构：北京联合大学北京市信息服务工程重点实验室

通讯机构：[1]corresponding author), Beijing Union Univ, Beijing Key Lab Informat Serv, Beijing, Peoples R China.|[11417103]北京联合大学北京市信息服务工程重点实验室;[11417]北京联合大学;

会议论文集：15th International Conference on Computational Intelligence and Security (CIS)

会议日期：DEC 13-16, 2019

会议地点：Macao, PEOPLES R CHINA

语种：英文

外文关键词：LIDAR SLAM; NDT; PLICP; point cloud registration; localization

摘要：LIDAR SLAM technology is an important way for accurate navigation of automatic vehicles, and it is also a prerequisite for the safe driving of automatic vehicles in the unstructured road environment of complex parks. This paper proposes a new Lidar fast point cloud registration algorithm that can realize fast and accurate localization and mapping of automatic vehicle point clouds through combination of Normal Distribution Transform (NDT) and Point-to-Line Iterative Closest Point (PLICP). First, the NDT point cloud registration algorithm is applied for rough registration of point clouds between adjacent frames, to achieve a rough estimate of the pose of automatic vehicles. Then, the PLICP point cloud registration algorithm is adopted to correct the rough registration result of point cloud. This step completes the precise registration of the point cloud and will achieve an accurate estimate of the pose of the automatic vehicle. Finally, the cloud registration is accumulated over time, and the point cloud information is continuously updated to complete the construction of the point cloud map.