A Real-Time 3DGS-SLAM with Voxel-based Memory Management and Region of Interest-based Pixel-wise Skipping Architecture on Edge Device

This work presents a real-time 3D Gaussian Splatting-based SLAM (3DGS-SLAM) accelerator to support high-quality dense mapping in mobile environments. There are two main hardware challenges for 3DGS-SLAM acceleration; 1) Large power consumption due to non-uniform memory access and 2) Excessive α-computation caused by processing unnecessary pixels. To solve these issues, two key building blocks are integrated in the proposed 3DGS-SLAM accelerator. First, a Voxel-based Gaussian Management (VGM) divides the entire scene into multiple voxels enabling selective Gaussian fetching with streaming off-chip memory access. This method reduces external memory access by 26.2%. Second, ROI-based Pixel-wise Skipping (RPS) reduces 68.3 % of α-computation by skipping unnecessary pixels outside of ROI. As a result, the proposed 3DGS-SLAM accelerator is implemented on Intel’s Cyclone V with a maximum clock frequency of 200 MHz. Evaluating on Replica dataset, it achieves 15.2 FPS 3DGS-SLAM enabling high-quality dense mapping on mobile devices.