Publications

Conference and Journal Papers

M. Schuck, S. Samy, A. P. Schoellig “A Primer on SO(3) Action Representations in Deep Reinforcement Learning,” in The Fourteenth International Conference on Learning Representations (ICLR), 2026. [paper]

M. Schuck, D. O. Dahanaggamaarachchi, B. Sprenger, V. Vyas, S. Zhou and A. P. Schoellig, “SwarmGPT: Combining Large Language Models With Safe Motion Planning for Drone Swarm Choreography,” in IEEE Robotics and Automation Letters, vol. 10, no. 11, pp. 12237-12244, 2025. [paper]

M. Schuck, J. Brüdigam, S. Hirche, A. P. Schoellig “Reinforcement Learning with Lie Group Orientations for Robotics,” in IEEE International Conference on Robotics and Automation (ICRA), 2025. [paper]

S. Teetaert, W. Zhao, A. Loquercio, S. Zhou, L. Brunke, M. Schuck, W. Hönig, J. Panerati, A. P. Schoellig, “Advancing Reproducibility, Benchmarks, and Education with Remote Sim2real,” in IEEE Robotics & Automation Magazine, vol. 32, no. 1, pp. 117-123, March 2025. [paper]

J. Brüdigam, M. Schuck, A. Capone, S. Sosnowski, S. Hirche “Structure-Preserving Learning Using Gaussian Processes and Variational Integrators,” in Proceedings of The 4th Annual Learning for Dynamics and Control Conference, 2022 [paper]

Workshop Papers

M. Schuck, A. v. Rohr, A. P. Schoellig “scipy.spatial.transform: Differentiable Framework-Agnostic 3D Transformations in Python,” in 1st Workshop on Differentiable Systems and Scientific Machine Learning, EurIPS, 2025. [preprint]

R. Römer, L. Brunke, M. Schuck, A. P. Schoellig “Safe Offline Reinforcement Learning using Trajectory-Level Diffusion Models,” in Workshop Back to the Future: Robot Learning Going Probabilistic, ICRA, 2024 . [preprint]