Momchil S. Tomov — accepted AI-conference papers

2025

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

Marc Heim, Francisco Suárez-Ruiz, Ishraq Bhuiyan, Bruno Brito, Momchil S. Tomov

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 2 Source ↗Scholar ↗

2023

DriveIRL: Drive in Real Life with Inverse Reinforcement Learning

Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu, Momchil S. Tomov, Robert E. Beaudoin, Sang Uk Lee +7

ICRA 2023poster

In this paper, we introduce the first published planner to drive a car in dense, urban traffic using Inverse Reinforcement Learning (IRL). Our planner, DriveIRL, generates a diverse set of trajectory proposals and scores them with a learned model. The best trajectory is tracked by our self-driving v…

Cited by 32 Source ↗Scholar ↗