GS-GVINS: A Tightly-integrated GNSS-Visual-Inertial Navigation System Augmented by 3D Gaussian Splatting
Recently, the emergence of 3D Gaussian Splatting (3DGS) has drawn significant attention in the area of 3D map reconstruction and visual SLAM. While extensive research has explored 3DGS for indoor trajectory tracking using visual sensor alone or in combination with Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU), its integration with GNSS for large-scale outdoor navigation remains underexplored. To address these concerns, we proposed GS-GVINS: a tightly-integrated GNSS-Visual-Inertial Navigation System augmented by 3DGS. This system leverages 3D Gaussian as a continuous differentiable scene representation in largescale outdoor environments, enhancing navigation performance through the constructed 3D Gaussian map. Notably, GS-GVINS is the first GNSS-Visual-Inertial navigation application that directly utilizes the analytical jacobians of SE3 camera pose with respect to 3D Gaussians. To maintain the quality of 3DGS rendering in extreme dynamic states, we introduce a motionaware 3D Gaussian pruning mechanism, updating the map based on relative pose translation and the accumulated opacity along the camera ray. For validation, we test our system under different driving environments: open-sky, sub-urban, and urban. Both self-collected and public datasets are used for evaluation. The results demonstrate the effectiveness of GS-GVINS in enhancing navigation accuracy across diverse driving environments.
最近，3D高斯溅射（3DGS）的出现引起了在3D地图重建和视觉SLAM领域的广泛关注。尽管已有大量研究探讨了单独使用视觉传感器或与激光雷达（LiDAR）和惯性测量单元（IMU）结合使用的3DGS在室内轨迹跟踪中的应用，但其与全球导航卫星系统（GNSS）结合用于大规模户外导航的研究仍然较少。为了解决这一问题，我们提出了GS-GVINS：一种由3DGS增强的紧密集成GNSS-视觉-惯性导航系统。该系统利用3D高斯作为大规模户外环境中连续可微的场景表示，通过构建的3D高斯地图提高导航性能。值得注意的是，GS-GVINS是首个直接利用SE3相机位姿相对于3D高斯的解析雅可比矩阵的GNSS-视觉-惯性导航应用。为了保持在极端动态状态下3DGS渲染的质量，我们引入了一种运动感知的3D高斯修剪机制，根据相对位姿平移和沿相机光线的累积不透明度更新地图。为了验证我们的系统，我们在不同的驾驶环境下进行了测试：开阔天空、郊区和城市环境。我们使用了自收集的数据集和公开数据集进行评估。结果表明，GS-GVINS在提高不同驾驶环境下的导航精度方面非常有效。