FGO-SLAM++: Real-Time Geometry-Aware Gaussian SLAM With Continuous Opacity Field

We present FGO-SLAM++, a real-time geometry-aware Gaussian SLAM system capable of processing video streams from arbitrary modalities. The system performs multi-view consistent map reconstruction by maintaining a continuous opacity field. Existing Gaussian SLAM systems face challenges in achieving efficient tracking and mapping while supporting multiple input modalities, which often necessitates a trade-off between rendering quality and geometric accuracy. This study demonstrates that it is possible to satisfy all these requirements simultaneously using video streams of arbitrary modalities. The core of the proposed method involves explicit geometric feature extraction to capture the underlying scene structure and estimate camera poses, followed by a Gaussian-based ray tracing strategy to construct and optimize an opacity field. Upon the detection of loop closures, the system performs global adjustment to enhance map consistency. Furthermore, the surface is directly extracted using the marching tetrahedra method and refined through a geometric constraint field. Extensive experiments demonstrate that the proposed method achieves superior performance in tracking accuracy, rendering quality, geometric reconstruction, and real-time efficiency.