← Search

Marc Heim

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

Lab2Car: A Versatile Wrapper for Deploying Experimental Planners in Complex Real-World Environments

ICRA 2025

Human-level autonomous driving is an ever-elusive goal, with planning and decision making - the cognitive functions that determine driving behavior - posing the greatest challenge. Despite a proliferation of promising approaches, progress is stifled by the difficulty of deploying experimental planne

Cited by 2SourceScholar