From the 1 of 7 linked papers with an AI index.
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RaDiVe: Robust 4D Radar Odometry with Distance-Bounded NDT and Velocity-Discrepancy Point Uncertainty
Sangwoo Jung, Dongjae Lee, Chiyun Noh +1
The paper presents RaDiVe, a 4D radar odometry system that improves registration accuracy and robustness by using a distance‑bounded NDT, a velocity‑discrepancy point uncertainty m…
TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory
Minwoo Jung, Dongjae Lee, Nived Chebrolu +3
Reliable localization is essential for sustainable forest management, as it allows robots to revisit and monitor the status of individual trees over long periods. In modern forestr…
LAPS: Improving Incremental LiDAR Mapping using Active Pooling and Sampling for Neural Distance Fields
Dongjae Lee, Wooseong Yang, Yifu Tao +2
Neural distance fields offer a compact and continuous representation of 3D geometry, making them attractive for incremental LiDAR mapping. However, their online optimization is vul…
Geometrically-Constrained Radar-Inertial Odometry via Continuous Point-Pose Uncertainty Modeling
Wooseong Yang, Dongjae Lee, Minwoo Jung +1
Radar odometry is crucial for robust localization in challenging environments; however, the sparsity of reliable returns and distinctive noise characteristics impede its performanc…
The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes
Hyunho Song, Dongjae Lee, Seunghun Oh +2
Large-scale construction and demolition significantly challenge long-term place recognition (PR) by drastically reshaping urban and suburban environments. Existing datasets predomi…
Ephemerality meets LiDAR-based Lifelong Mapping
Hyeonjae Gil, Dongjae Lee, Giseop Kim +1
Lifelong mapping is crucial for the long-term deployment of robots in dynamic environments. In this paper, we present ELite, an ephemerality-aided LiDAR-based lifelong mapping fram…