A fabricated 16nm SoC that performs real-time 3D occupancy mapping under 6 mW, reducing query energy by over 80%.
April 1, 2026
Original Paper
Gleanmer: A 6 mW SoC for Real-Time 3D Gaussian Occupancy Mapping
arXiv · 2603.29005
The Takeaway
This represents a major milestone for bringing high-fidelity spatial intelligence to the extreme edge (e.g., AR glasses or micro-drones). It demonstrates that co-optimizing Gaussian-based mapping with dedicated hardware enables sophisticated 3D perception at near-zero power budgets.
From the abstract
High-fidelity 3D occupancy mapping is essential for many edge-based applications (such as AR/VR and autonomous navigation) but is limited by power constraints. We present Gleanmer, a system on chip (SoC) with an accelerator for GMMap, a 3D occupancy map using Gaussians. Through algorithm-hardware co-optimizations for direct computation and efficient reuse of these compact Gaussians, Gleanmer reduces construction and query energy by up to 63% and 81%, respectively. Approximate computation on Gaus