3 papers
cs.RO2026
MILER: Semantic Mid-Level Representation for Sim-to-Real Reinforcement Learning in Unstructured Autonomous Driving
Thomas Steinecker, Denis Trescher, Alexander Bienemann +2
Reinforcement learning constitutes a promising approach owing to its potential for superhuman performance and self-learned policies. However, its application to real-world autonomo…
cs.RO2025
Dynamics-Decoupled Trajectory Alignment for Sim-to-Real Transfer in Reinforcement Learning for Autonomous Driving
Thomas Steinecker, Alexander Bienemann, Denis Trescher +2
Reinforcement learning (RL) has shown promise in robotics, but deploying RL on real vehicles remains challenging due to the complexity of vehicle dynamics and the mismatch between…
cs.RO2024
Collision Probability Distribution Estimation via Temporal Difference Learning
Thomas Steinecker, Thorsten Luettel, Mirko Maehlisch
We introduce CollisionPro, a pioneering framework designed to estimate cumulative collision probability distributions using temporal difference learning, specifically tailored to a…