Abstract
We propose a tightly-coupled LiDAR/Polarization Vision/Inertial/Magnetometer/Optical Flow Odometry via Smoothing and Mapping (LPVIMO-SAM) framework, which integrates LiDAR, polarization vision, inertial measurement unit, magnetometer, and optical flow in a tightly-coupled fusion. This framework enables high-precision and highly robust real-time state estimation and map construction in challenging environments, such as LiDAR-degraded, low-texture regions, and feature-scarce areas. The LPVIMO-SAM comprises two subsystems: a Polarized Vision-Inertial System and a LiDAR/Inertial/Magnetometer/Optical Flow System. The polarized vision enhances the robustness of the Visual/Inertial odometry in low-feature and low-texture scenarios by extracting the polarization information of the scene. The magnetometer acquires the heading angle, and the optical flow obtains the speed and height to reduce the accumulated error. A magnetometer heading prior factor, an optical flow speed observation factor, and a height observation factor are designed to eliminate the cumulative errors of the LiDAR/Inertial odometry through factor graph optimization. Meanwhile, the LPVIMO-SAM can maintain stable positioning even when one of the two subsystems fails, further expanding its applicability in LiDAR-degraded, low-texture, and low-feature environments. Code is available on this https URL.
Abstract (translated)
我们提出了一种基于平滑与映射（Smoothing and Mapping，SAM）的紧密耦合激光雷达/偏振视觉/惯性/磁力计/光流里程计框架（LPVIMO-SAM）。该框架集成了激光雷达、偏振视觉系统、惯性测量单元、磁力计和光流，并实现了紧密融合。此框架能够在复杂环境中实现高精度和高度鲁棒的实时状态估计与地图构建，包括在激光雷达性能下降、低纹理区域以及特征稀疏地区等挑战性条件下。 LPVIMO-SAM由两个子系统组成：偏振视觉/惯性系统（Polarized Vision-Inertial System）和激光雷达/惯性/磁力计/光流系统。其中，偏振视觉增强了在低特征与低纹理场景中视觉/惯性里程计的鲁棒性，通过提取场景中的偏振信息来实现这一点；磁力计获取航向角数据，而光流则用于获取速度和高度以减少累积误差。设计了磁力计航向先验因子、光流速度观测因子以及高度观测因子，通过图优化方法消除激光雷达/惯性里程计的累积误差。 此外，即使其中一个子系统失效时，LPVIMO-SAM仍能保持稳定定位性能，进一步扩展了其在激光雷达性能受限、低纹理和特征稀疏环境中的应用范围。相关代码可在此网址获取：[https URL]（原文中给出的链接未提供具体地址）。
URL
https://arxiv.org/abs/2504.20380
