LoopSplat: Loop Closure by Registering 3D Gaussian Splats

Understand

Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian Splats (3DGS) has recently shown promise towards more accurate, dense 3D scene maps.

• However, existing 3DGS-based methods fail to address the global consistency of the scene via loop closure and/or global bundle adjustment.
• To this end, we propose LoopSplat, which takes RGB-D images as input and performs dense mapping with 3DGS submaps and frame-to-model tracking.
• LoopSplat triggers loop closure online and computes relative loop edge constraints between submaps directly via 3DGS registration, leading to improvements in efficiency and accuracy over traditional global-to-local point cloud registration.