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This work presents GINIO, a geometric SO(3)-equivariant interface for neural inertial odometry under arbitrary rotations of the IMU measurement frame, and introduces Last-Frame Alignment (LFA), a deterministic preprocessing step that is provably equivalent to world-frame training for SO(3)-equivariant predictors.
Rigid body trajectory optimization can now avoid singularities and achieve faster convergence with a new structure-aware method that respects the underlying geometry.
