Gaussian Splatting SLAM

Gaussian Splatting SLAM is a novel approach to simultaneous localization and mapping (SLAM) that leverages 3D Gaussian splatting for creating photorealistic, dense 3D scene reconstructions in real-time. Current research focuses on improving the robustness and efficiency of this technique, addressing challenges like drift accumulation through loop closure mechanisms and optimizing the representation of the scene using hierarchical structures and compact Gaussian models. This approach holds significant promise for advancing robotics and augmented reality applications by enabling accurate, high-fidelity 3D mapping and rendering, particularly in dynamic environments with semantic understanding.