PVL-Cartographer:基于全景视觉辅助激光雷达制图器的SLAM,用于Maverick移动制图系统

Remote. Sens. Pub Date : 2023-07-03 DOI:10.3390/rs15133383
Yujia Zhang, Jungwon Kang, G. Sohn
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引用次数: 1

摘要

移动地图系统(MMS)在生成精确的3D地图方面发挥着至关重要的作用。然而,利用倾斜激光雷达(光探测和测距)的传统MMS在捕获全面的环境数据方面存在局限性。我们提出了MMS的“PVL-Cartographer”SLAM (Simultaneous Localization And Mapping)方法来解决这些限制。该系统包含多个传感器,可实现可靠、精确的地图定位。它包括两个子系统:早期融合和中间融合。在早期的融合中,距离地图是由全景图像空间中的LiDAR点创建的,简化了视觉特征的整合。SLAM系统可适应具有和不具有增强范围的视觉特征。在中间融合中,使用姿态图合并相机和LiDAR节点,节点之间的约束来自IMU(惯性测量单元)数据。在具有挑战性的户外环境中进行的全面测试表明,即使在特征稀缺的环境中,所提出的SLAM系统也可以产生值得信赖的结果。最终,我们建议的PVL-Cartographer系统有效而准确地解决了MMS定位和制图挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PVL-Cartographer: Panoramic Vision-Aided LiDAR Cartographer-Based SLAM for Maverick Mobile Mapping System
The Mobile Mapping System (MMS) plays a crucial role in generating accurate 3D maps for a wide range of applications. However, traditional MMS that utilizes tilted LiDAR (light detection and ranging) faces limitations in capturing comprehensive environmental data. We propose the “PVL-Cartographer” SLAM (Simultaneous Localization And Mapping) approach for MMS to address these limitations. This proposed system incorporates multiple sensors to yield dependable and precise mapping and localization. It consists of two subsystems: early fusion and intermediate fusion. In early fusion, range maps are created from LiDAR points within a panoramic image space, simplifying the integration of visual features. The SLAM system accommodates both visual features with and without augmented ranges. In intermediate fusion, camera and LiDAR nodes are merged using a pose graph, with constraints between nodes derived from IMU (Inertial Measurement Unit) data. Comprehensive testing in challenging outdoor settings demonstrates that the proposed SLAM system can generate trustworthy outcomes even in feature-scarce environments. Ultimately, our suggested PVL-Cartographer system effectively and accurately addresses the MMS localization and mapping challenge.
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