We are excited about our contribution to the Robotics & Automation Letters (RA-L). Congratulations to the authors!
Learning-based Nonlinear Model Predictive Control of Articulated Soft Robots using Recurrent Neural Networks. Hendrik Schäfke, Tim-Lukas Habich, Christian Muhmann, Simon F. G. Ehlers, Thomas Seel, Moritz Schappler
In this paper, we present a data-based nonlinear model predictive control (NMPC) that uses recurrent neural networks as a model. This captures complex, nonlinear effects such as hysteresis and enables precise control of soft robots.
We would like to thank the entire team, especially Hendrik Schäfke and Tim-Lukas Habich, for their dedicated work on this project. Your co-operation and hard work has played a crucial role in this success.
You can find more information here: https://doi.org/10.48550/arXiv.2411.05616