AutonomousDriving

SatMap: Satellite-guided HD maps for safer self-driving

Kari Jaaskelainen

16 Jan 2026 — 1 min read

SatMap in a nutshell

What if self-driving cars could borrow a bird’s-eye view? SatMap fuses multi-view camera feeds with satellite imagery to build online, vectorized HD maps that planning and prediction modules can use on the fly.

Addresses camera limits like depth ambiguity and occlusion using lane-level semantics and texture from satellite maps as a global prior.
Directly outputs a vectorized HD map from a BEV perspective.
On the nuScenes benchmark: +34.8% mAP vs camera-only, +8.5% vs camera+LiDAR fusion; advantages persist at long range and in adverse weather.

Why it matters: more reliable situational awareness without depending solely on expensive, close-range sensors.

Paper: https://arxiv.org/abs/2601.10512v1

Code (coming soon): https://iv.ee.hm.edu/satmap/

Paper: https://arxiv.org/abs/2601.10512v1

Register: https://www.AiFeta.com

AutonomousDriving ComputerVision HDMaps SatelliteImagery BEV Robotics AI Mapping nuScenes SelfDriving

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