论文标题
SC-LIDAR-SLAM：前端不可知论的雷达大满贯系统
SC-LiDAR-SLAM: a Front-end Agnostic Versatile LiDAR SLAM System
论文作者
论文摘要
准确的3D点云图生成是各种机器人任务甚至数据驱动的城市分析的核心任务。为此，已经阐述了基于光（激光雷达）传感器的同时定位和映射（SLAM）技术。为了组成一个完整的大满贯系统，在学术界已独立提出了许多探测器和位置识别方法。但是，它们几乎没有被整合或太紧密组合，因此交换（升级）单一探针或位置识别模块非常努力。最近，每个模块的性能得到了很多改进，因此有必要构建一个可以有效整合它们并轻松地将它们与最新的系统集成在一起的系统。在本文中，我们发布了这样的前端不可知论激光雷达大满贯系统，名为SC-LIDAR-SLAM。我们通过设计模块化来构建一个完整的SLAM系统，并成功地将其与扫描上下文++集成在一起，并多样化现有的OpenSource LiDAR ODMOTIRENED方法来生成准确的点云图。
Accurate 3D point cloud map generation is a core task for various robot missions or even for data-driven urban analysis. To do so, light detection and ranging (LiDAR) sensor-based simultaneous localization and mapping (SLAM) technology have been elaborated. To compose a full SLAM system, many odometry and place recognition methods have independently been proposed in academia. However, they have hardly been integrated or too tightly combined so that exchanging (upgrading) either single odometry or place recognition module is very effort demanding. Recently, the performance of each module has been improved a lot, so it is necessary to build a SLAM system that can effectively integrate them and easily replace them with the latest one. In this paper, we release such a front-end agnostic LiDAR SLAM system, named SC-LiDAR-SLAM. We built a complete SLAM system by designing it modular, and successfully integrating it with Scan Context++ and diverse existing opensource LiDAR odometry methods to generate an accurate point cloud map
