3 papers
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…
eess.SY2026
Signal Temporal Logic Evaluation and Synthesis Using Deep Reachability Analysis and Layered Control Architecture
Joonwon Choi, Kartik Anand Pant, Youngim Nam +3
We propose a signal temporal logic (STL)-based framework that checks the feasibility of a mission described in STL and synthesizes control to safely execute it. The proposed framew…
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…