文献类型：期刊文献

英文题名：A Hybrid Loop Closure Detection Method Based on Lidar SLAM

作者：Mengna, Chai[1]; Yuansheng, Liu[2]

第一作者：Mengna, Chai

机构：[1] Smart City College, Beijing Union University, Beijing, China; [2] College of Robotics, Beijing Union University, Beijing, China

第一机构：北京联合大学智慧城市学院

年份：2019

起止页码：301-305

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

收录：EI(收录号：20201308355538)

语种：英文

外文关键词：Mapping - Intelligent vehicle highway systems - Autonomous vehicles

摘要：Simultaneous localization and mapping (SLAM) is the key technology to realize self-localization of autonomous vehicles. However, the lidar SLAM with traditional loop closure detection cannot obtain reliable accuracy and real-time under large scale scene due to the accumulated error of point cloud registration. In this paper, a hybrid loop closure detection (HLCD) method based on spatial location and appearance similarity is proposed and introduced into lidar SLAM technology. An experimental test is implemented on the platform of autonomous vehicle to verify the correctness and feasibility of theoretical design. Experimental results show that the proposed method can effectively reduce the cumulative deviation and time consuming. ? 2019 IEEE.