| Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes AR Geist, S Trimpe Proceedings of Machine Learning Research 120, 225--234, 2020 | 23 | 2020 |
| Embedded spherical localization for micro underwater vehicles based on attenuation of electro-magnetic carrier signals DA Duecker, AR Geist, M Hengeler, E Kreuzer, MA Pick, V Rausch, ... Sensors 17 (5), 959, 2017 | 20 | 2017 |
| Structured learning of rigid‐body dynamics: A survey and unified view from a robotics perspective AR Geist, S Trimpe GAMM‐Mitteilungen 44 (2), e202100009, 2021 | 19 | 2021 |
| Learning environmental field exploration with computationally constrained underwater robots: Gaussian processes meet stochastic optimal control DA Duecker, AR Geist, E Kreuzer, E Solowjow Sensors 19 (9), 2094, 2019 | 18 | 2019 |
| Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics AR Geist, A Hackbarth, E Kreuzer, V Rausch, M Sankur, E Solowjow 2016 IEEE International Conference on Robotics and Automation (ICRA), 4551-4556, 2016 | 15 | 2016 |
| Using physics knowledge for learning rigid-body forward dynamics with gaussian process force priors L Rath, AR Geist, S Trimpe Conference on robot learning, 101-111, 2022 | 12 | 2022 |
| Data collection for robust end-to-end lateral vehicle control AR Geist, A Hansen, E Solowjow, S Yang, E Kreuzer Dynamic Systems and Control Conference 58271, V001T45A007, 2017 | 8 | 2017 |
| The wheelbot: A jumping reaction wheel unicycle AR Geist, J Fiene, N Tashiro, Z Jia, S Trimpe IEEE Robotics and Automation Letters 7 (4), 9683-9690, 2022 | 7 | 2022 |
| Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations S Mamedov, AR Geist, J Swevers, S Trimpe arXiv preprint arXiv:2307.07975, 2023 | 1* | 2023 |
| Learning with 3D rotations, a hitchhiker's guide to SO (3) AR Geist, J Frey, M Zobro, A Levina, G Martius arXiv preprint arXiv:2404.11735, 2024 | | 2024 |
| Physics-informed regression of implicitly-constrained robot dynamics AR Geist | | 2022 |
| Supplementary Material-of-Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors L Rath, AR Geist, S Trimpe | | |
Sebastian TrimpeProfessor, RWTH Aachen UniversityVerified email at dsme.rwth-aachen.de
