GINIO: A Geometric SO(3)-Equivariant Interface for Neural Inertial Odometry
Neural inertial odometry increasingly uses networks as learned measurements inside filtering pipelines. Such measurements should transform consistently under arbitrary IMU mounting conventions: their mean must transform as a vector, and their covariance must transform congruently as a second-order tensor. We present GI...
Chan-Ki Kim, Ming-Han Zhu, Tzu-Yuan Lin et al.
· 0 citations