3 papers
eess.SY2024
Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models
Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen +4
Achieving global optimality in nonlinear model predictive control (NMPC) is challenging due to the non-convex nature of the underlying optimization problem. Since commonly employed…
cs.RO2024
Reinforcement Learning with Lie Group Orientations for Robotics
Martin Schuck, Jan Brüdigam, Sandra Hirche +1
Handling orientations of robots and objects is a crucial aspect of many applications. Yet, ever so often, there is a lack of mathematical correctness when dealing with orientations…
cs.RO2020
Linear-Time Variational Integrators in Maximal Coordinates
Jan Brüdigam, Zachary Manchester
Most dynamic simulation tools parameterize the configuration of multi-body robotic systems using minimal coordinates, also called generalized or joint coordinates. However, maximal…