16 citations · 29 across the 19 of their papers we have counts for
5 papers · 1 filter
Learning-based Nonlinear Model Predictive Control of Articulated Soft Robots using Recurrent Neural Networks
Hendrik Schäfke, Tim-Lukas Habich, Christian Muhmann +3
Soft robots pose difficulties in terms of control, requiring novel strategies to effectively manipulate their compliant structures. Model-based approaches face challenges due to th…
Predictive Energy Management for Recuperation Axles in Refrigerated Trailers
Dennis Bank, Simon F. G. Ehlers, Karl-Philipp Kortmann +3
Refrigerated truck trailers are currently mainly operated with environmentally harmful diesel units; an alternative is to operate the refrigeration unit with electrical energy. How…
Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline
Jan-Hendrik Ewering, Björn Volkmann, Simon F. G. Ehlers +2
Intelligent real-world systems critically depend on expressive information about their system state and changing operation conditions, e.g., due to variation in temperature, locati…
Towards Optimized Parallel Robots for Human-Robot Collaboration by Combined Structural and Dimensional Synthesis
Aran Mohammad, Thomas Seel, Moritz Schappler
Parallel robots (PR) offer potential for human-robot collaboration (HRC) due to their lower moving masses and higher speeds. However, the parallel leg chains increase the risks of…
Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems
Henrik Krauss, Tim-Lukas Habich, Max Bartholdt +2
Physics-informed neural networks (PINNs) are trained using physical equations and can also incorporate unmodeled effects by learning from data. PINNs for control (PINCs) of dynamic…