4 citations · 8 across the 6 of their papers we have counts for
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cs.RO2026
Kernel-Based Metrics Learning for Uncertain Opponent Vehicle Trajectory Prediction in Autonomous Racing
Hojin Lee, Youngim Nam, Sanghun Lee +1
Autonomous racing confronts significant challenges in safely overtaking Opponent Vehicles (OVs) that exhibit uncertain trajectories, stemming from unknown driving policies. To addr…
cs.RO2026
Continual Learning for Traversability Prediction with Uncertainty-Aware Adaptation
Hojin Lee, Yunho Lee, Daniel A Duecker +1
Traversability prediction is a critical component of autonomous navigation in unstructured environments, where complex and uncertain robot-terrain interactions pose significant cha…
cs.RO2026
Track-centric Iterative Learning for Global Trajectory Optimization in Autonomous Racing
Youngim Nam, Jungbin Kim, Kyungtae Kang +1
This paper presents a global trajectory optimization framework for minimizing lap time in autonomous racing under uncertain vehicle dynamics. Optimizing the trajectory over the ful…