Journal Articles
Semantically Safe Robot Manipulation: From Semantic Scene Understanding to Motion Safeguard
L. Brunke, Y. Zhang, R. Römer, J. Naimer, S. Zhou, A. P. Schoellig
IEEE Robotics and Automation Letters (RA-L), 2025
[Paper] [arXiv] [Video] [Website]
Vision-Based Uncertainty-Aware Motion Planning based on Probabilistic Semantic Segmentation
R. Römer*, A. Lederer*, S. Tesfazgi, S. Hirche
IEEE Robotics and Automation Letters (RA-L), 2023
[Paper] [arXiv] [Video]
Conference Papers
Diffusion Predictive Control with Constraints
R. Römer, A. von Rohr, A. P. Schoellig
Learning for Dynamics & Control Conference (L4DC), 2025
[Paper] [arXiv]
Flying through Moving Gates without Full State Estimation
R. Römer, T. Emmert, A. P. Schoellig
IEEE International Conference on Robotics and Automation (ICRA), 2025
[arXiv]
Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems
R. Römer, L. Brunke, S. Zhou, A. P. Schoellig
American Control Conference (ACC), 2024
[Paper] [arXiv] [Video]
Catching Objects with a Robot Arm using Model Predictive Control
T. Gold, R. Römer, A. Völz, K. Graichen
American Control Conference (ACC), 2022
[Paper] [Video]
Workshop Papers
Safe Offline Reinforcement Learning using Trajectory-Level Diffusion Models
R. Römer, L. Brunke, M. Schuck, A. P. Schoellig
ICRA Workshop—Back to the Future: Robot Learning Going Probabilistic, 2024
[Paper]
Theses
The Role of Control Frequency for the Stability and Closed-Loop Performance of Uncertain Systems
R. Römer
Master Thesis at TU Munich, 2023
[PDF]
Supervisors: Lukas Brunke, Dr. SiQi Zhou, Prof. Angela P. Schoellig
Workshops
Workshop on Robot Manipulation in a World of Abundant Data
A. P. Schoellig, A. Garg, K. Pereida, O. Mees, R. Römer, M. Schuck, S. Zhou
Conference on Robot Learning (CoRL), 2024
[Website]
