Presents the first radar bundle adjustment framework using Gaussian Splatting, integrated with a radar-inertial frontend to reduce average translational and rotational errors by 90% and 80% across indoor scenes.
Multi-class road user detection with 3+ 1d radar in the view-of- delft dataset
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment
Presents the first radar bundle adjustment framework using Gaussian Splatting, integrated with a radar-inertial frontend to reduce average translational and rotational errors by 90% and 80% across indoor scenes.