L2Calib uses reinforcement learning with a Bingham-distribution rotation policy and trajectory-alignment reward to estimate LiDAR-IMU extrinsics, showing promise under weak motion excitation.
A general approach to spatiotemporal calibration in multisensor systems
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L2Calib: $SE(3)$-Manifold Reinforcement Learning for Robust Extrinsic Calibration with Degenerate Motion Resilience
L2Calib uses reinforcement learning with a Bingham-distribution rotation policy and trajectory-alignment reward to estimate LiDAR-IMU extrinsics, showing promise under weak motion excitation.