54 citations · 54 across the 4 of their papers we have counts for
4 papers
ALIVE-LIO: Degeneracy-Aware Learning of Inertial Velocity for Enhancing ESKF-Based LiDAR-Inertial Odometry
Seongjun Kim, Daehan Lee, Junwoo Hong +3
Odometry estimation using light detection and ranging (LiDAR) and an inertial measurement unit (IMU), known as LiDAR-inertial odometry (LIO), often suffers from performance degrada…
Benchmarking Visual Feature Representations for LiDAR-Inertial-Visual Odometry Under Challenging Conditions
Eunseon Choi, Junwoo Hong, Daehan Lee +9
Accurate localization in autonomous driving is critical for successful missions including environmental mapping and survivor searches. In visually challenging environments, includi…
GenZ-LIO: Generalizable LiDAR-Inertial Odometry Beyond Confined--Open Boundaries
Daehan Lee, Hyungtae Lim, Seongjun Kim +7
For field robotic missions such as inspection, search-and-rescue, and exploration, light detection and ranging (LiDAR)-inertial odometry (LIO) can serve as a core component of auto…
GenZ-ICP: Generalizable and Degeneracy-Robust LiDAR Odometry Using an Adaptive Weighting
Daehan Lee, Hyungtae Lim, Soohee Han
Light detection and ranging (LiDAR)-based odometry has been widely utilized for pose estimation due to its use of high-accuracy range measurements and immunity to ambient light con…