Localization and Neural Splatting on the Edge: An FPGA Scene Memory for Robots
Resource-constrained robots and autonomous vehicles need scene memories that localize a camera and render nearby views without a desktop GPU. Scene-coordinate regression (SCR) and 3D Gaussian splatting (3DGS) fit because they avoid an SfM stage, but ACEsplat-style pipelines are GPU-centered, and moving them to an edge FPGA is hard because SCR is pose-sensitive and 3DGS rendering is irregular and capacity-sensitive. We present LENS, an edge scene-memory acceleration system on the AMD KR260 that brings an ACEsplat-style workload to a low-power FPGA/ARM platform. Rather than proposing a new scene model, LENS co-designs the two dominant kernels with the board data path: an INT16 SCR accelerat...
| Authors | Que Haohua, Mingkai Liu, Handong Yao |
|---|---|
| Primary category | cs.RO |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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