Trajectory tracking of an omnidirectional mobile robot using Gaussian process regression H Eschmann, H Ebel, P Eberhard at-Automatisierungstechnik 69 (8), 656-666, 2021 | 13 | 2021 |
Data-based model of an omnidirectional mobile robot using Gaussian processes H Eschmann, H Ebel, P Eberhard IFAC-PapersOnLine 54 (7), 13-18, 2021 | 8 | 2021 |
Gaussian process regression-augmented nonlinear model predictive control for quadrotor object grasping W Luo, H Eschmann, P Eberhard 2022 International Conference on Unmanned Aircraft Systems (ICUAS), 11-19, 2022 | 3 | 2022 |
Identification of friction models for mpc-based control of a powercube serial robot J Fehr, A Kargl, H Eschmann arXiv preprint arXiv:2203.10896, 2022 | 3 | 2022 |
Learning‐based model predictive control for multi‐agent systems using Gaussian processes H Eschmann, P Eberhard PAMM 20 (1), e202000009, 2021 | 3 | 2021 |
On Koopman-based surrogate models for non-holonomic robots L Bold, H Eschmann, M Rosenfelder, H Ebel, K Worthmann arXiv preprint arXiv:2303.09144, 2023 | 2 | 2023 |
Exploration-exploitation-based trajectory tracking of mobile robots using Gaussian processes and model predictive control H Eschmann, H Ebel, P Eberhard Robotica 41 (10), 3040-3058, 2023 | 1 | 2023 |
High Accuracy Data-Based Trajectory Tracking of an Omnidirectional Mobile Robot H Eschmann, H Ebel, P Eberhard International Conference on Robotics in Alpe-Adria Danube Region, 420-427, 2022 | 1 | 2022 |