Light Detection And Ranging (LiDAR) technology has provided an impactful way to capture 3D data. However, consistent mapping in sensing-degenerated and perceptually-limited scenes (e.g. multi-story buildings) or under high dynamic sensor motion (e.g. rotating platform) remains a significant challenge. In this paper, we present OR-LIM, a novel observability-aware LiDAR-inertial-mapping system. Essentially, it combines a robust real-time LiDAR-inertial-odometry (LIO) module with an efficient surfel-map-smoothing (SMS) module that seamlessly optimizes the sensor poses and scene geometry at the same time. To improve robustness, the planar surfels are hierarchically generated and grown from point cloud maps to provide reliable correspondences for fixed-lag optimization. Moreover, the normals of surfels are analyzed for the observability evaluation of each frame. To maintain global consistency, a factor graph is utilized integrating the information from IMU propagation, LIO as well as the SMS. The system is extensively tested on the datasets collected by a low-cost multi-beam LiDAR (MBL) mounted on a rotating platform. The experiments with various settings of sensor motion, conducted on complex multi-story buildings and large-scale outdoor scenes, demonstrate the superior performance of our system over multiple state-of-the-art methods. The improvement of point accuracy reaches 3.39–13.6 % with an average 8.71 % outdoor and correspondingly 1.89–15.88 % with 9.09 % indoor, with reference to the collected Terrestrial Laser Scanning (TLS) map.

中文翻译：

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OR-LIM：高动态传感器运动下的可观测性感知鲁棒型 LiDAR 惯性映射


光探测和测距 （LiDAR） 技术提供了一种捕获 3D 数据的有效方法。然而，在传感退化和感知受限的场景（例如多层建筑）或高动态传感器运动（例如旋转平台）下实现一致的映射仍然是一个重大挑战。在本文中，我们提出了 OR-LIM，这是一种新型的可观测性感知 LiDAR 惯性映射系统。从本质上讲，它将强大的实时 LiDAR 惯性里程计 （LIO） 模块与高效的 surfel-map-smoothing （SMS） 模块相结合，可同时无缝优化传感器姿态和场景几何形状。为了提高稳健性，平面曲面从点云地图分层生成和增长，以便为固定滞后优化提供可靠的对应关系。此外，还分析了 surfels 的法线，以便对每帧进行可观察性评估。为了保持全局一致性，使用了因子图，集成了来自 IMU 传播、LIO 和 SMS 的信息。该系统在安装在旋转平台上的低成本多光束 LiDAR （MBL） 收集的数据上进行了广泛测试。在复杂的多层建筑和大型户外场景中对传感器运动的各种设置进行的实验，证明了我们的系统在多种最先进方法中的卓越性能。参考收集的地面激光扫描 （TLS） 地图，点精度的提高达到 3.39-13.6%，室外平均 8.71%，室内平均 1.89-15.88%，室内 9.09%。