14 citations · 19 across the 4 of their papers we have counts for
4 papers
Variational Integrators and Graph-Based Solvers for Multibody Dynamics in Maximal Coordinates
Jan Brüdigam, Stefan Sosnowski, Zachary Manchester +1
Multibody dynamics simulators are an important tool in many fields, including learning and control for robotics. However, many existing dynamics simulators suffer from inaccuracies…
Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control
Martin Schuck, Jan Brüdigam, Alexandre Capone +2
Reinforcement learning is a promising method for robotic grasping as it can learn effective reaching and grasping policies in difficult scenarios. However, achieving human-like man…
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators
Jan Brüdigam, Martin Schuck, Alexandre Capone +2
Gaussian process regression is increasingly applied for learning unknown dynamical systems. In particular, the implicit quantification of the uncertainty of the learned model makes…
Linear-Quadratic Optimal Control in Maximal Coordinates
Jan Brüdigam, Zachary Manchester
The linear-quadratic regulator (LQR) is an efficient control method for linear and linearized systems. Typically, LQR is implemented in minimal coordinates (also called generalized…