文献类型：期刊文献

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

作者：Qingshan, Wang[1]; Jun, Zhang[2]

第一作者：Qingshan, Wang

机构：[1] Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China; [2] College of Robotics, Beijing Union University, Beijing, 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

年份：2019

起止页码：132-136

外文期刊名：Proceedings - 2019 15th International Conference on Computational Intelligence and Security, CIS 2019

收录：EI(收录号：20201308355493)

语种：英文

外文关键词：Iterative methods - Surface measurement - Robotics - Optical radar

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. ? 2019 IEEE.