8 citations · 13 across the 3 of their papers we have counts for
3 papers
eess.SY2024★ 8 cited
Data-Driven Predictive Control of Nonholonomic Robots Based on a Bilinear Koopman Realization: Data Does Not Replace Geometry
Mario Rosenfelder, Lea Bold, Hannes Eschmann +3
Advances in machine learning and the growing trend towards effortless data generation in real-world systems has led to an increasing interest for data-inferred models and data-base…
cs.RO2023★ 1 cited
On Koopman-based surrogate models for non-holonomic robots
Lea Bold, Hannes Eschmann, Mario Rosenfelder +2
Data-driven surrogate models of dynamical systems based on the extended dynamic mode decomposition are nowadays well-established and widespread in applications. Further, for non-ho…
eess.SY2022★ 4 cited
Identification of Friction Models for MPC-based Control of a PowerCube Serial Robot
Jörg Fehr, Arnim Kargl, Hannes Eschmann
For model-based control, an accurate and in its complexity suitable representation of the real system is a decisive prerequisite for high and robust control quality. In a structure…