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Teawon Han

2 accepted papers

2026

TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning

ICRA 2026poster

We present TreeIRL, a novel planner for autonomous driving that combines Monte Carlo tree search (MCTS) and inverse reinforcement learning (IRL) to achieve state-of-the-art performance in simulation and in real-world driving. The key idea is to use MCTS to find a promising set of safe candidate traj…

2025

DaSP-RRT: Data-Driven Safe Performance-Aware Motion Planning

RA-L 2025

This letter presents a data-driven safe motion planning approach, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DaSP-RRT</monospace>, designed to generate collision-free paths with guaranteed optimality through the use of invariant sets. The pro

Cited by 2SourceScholar