2 papers
cs.RO2023
FF-LINS: A Consistent Frame-to-Frame Solid-State-LiDAR-Inertial State Estimator
Hailiang Tang, Tisheng Zhang, Xiaoji Niu +3
Most of the existing LiDAR-inertial navigation systems are based on frame-to-map registrations, leading to inconsistency in state estimation. The newest solid-state LiDAR with a no…
cs.RO2021
CTIN: Robust Contextual Transformer Network for Inertial Navigation
Bingbing Rao, Ehsan Kazemi, Yifan Ding +3
Recently, data-driven inertial navigation approaches have demonstrated their capability of using well-trained neural networks to obtain accurate position estimates from inertial me…