Prati
A. René Geist
A. René Geist
Postdoc, University of Tübingen
Potvrđena adresa e-pošte na uni-tuebingen.de - Početna stranica
Naslov
Citirano
Citirano
Godina
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
262021
Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes
AR Geist, S Trimpe
Proceedings of Machine Learning Research 120, 225--234, 2020
232020
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
222017
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
192019
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
182016
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
152022
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
142022
Learning with 3D rotations, a hitchhiker's guide to SO(3)
AR Geist, J Frey, M Zhobro, A Levina, G Martius
arXiv preprint arXiv:2404.11735, 2024
112024
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
82017
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 deformable linear object dynamics from a single trajectory
S Mamedov, AR Geist, R Viljoen, S Trimpe, J Swevers
arXiv preprint arXiv:2407.03476, 2024
2024
Physics-informed regression of implicitly-constrained robot dynamics
AR Geist
Dissertation, Stuttgart, Universität Stuttgart, 2022, 2022
2022
Supplementary Material-of-Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors
L Rath, AR Geist, S Trimpe
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