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.
Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large- scale and long-term online operation
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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.