MM3DGS SLAM: Multi-modal 3D Gaussian Splatting for SLAM Using Vision, Depth, and Inertial Measurements

Understand

Simultaneous localization and mapping is essential for position tracking and scene understanding.

• 3D Gaussian-based map representations enable photorealistic reconstruction and real-time rendering of scenes using multiple posed cameras.
• We show for the first time that using 3D Gaussians for map representation with unposed camera images and inertial measurements can enable accurate SLAM.
• Our method, MM3DGS, addresses the limitations of prior neural radiance field-based representations by enabling faster rendering, scale awareness, and improved trajectory tracking.