Henrik HoseM. Sc.
- Phone: +49 241 80-92058
Since April 2022, I am a PhD student with the DFG Research Training Group UnRAVeL under the supervision of Prof. Sebastian Trimpe at the Institute for Data Science in Mechanical Engineering. Before joining the DSME and UnRAVeL, I worked as a researcher in the Model-based Assembly Automation Group at the Laboratory for Machine Tools and Production Engineering (WZL). I received B.Sc. and M.Sc. degrees in Mechanical Engineering from RWTH Aachen University with semesters abroad at Georgia Tech and UC Berkeley.
Fast feedback responses, stability, and constraint satisfaction are critical requirements for control in robotics to ensure safety. Model predictive control (MPC) achieves stability and constraint satisfaction, but is notoriously slow to evaluate. Approximation of such MPC controllers via (deep) neural networks (NNs) allows for fast online evaluation. However, the approximation introduces inaccuracies that can cause instabilities or constraint violations. In this project, novel methods for offline validation and safe online evaluation of approximations of MPC type controllers are developed. This work builds upon existing results in statistical offline validation, online safety certification in control, and explores the use of formal verification methods. Novel approximate MPC schemes with offline validation and safe online evaluation methods are evaluated in real-world problems from the robotics domain, such as the Wheelbot.
The Wheelbot, a small reaction wheel balancing robot, was originally developed at the DSME and MPI-IS Stuttgart under the supervision of Prof. Sebastian Trimpe. A video of the Wheelbot is available here. The Wheelbot is a challenging robotics test bed for non-linear control when balancing, and even hybrid-systems with contact switches for stand-up maneuver. The next generation - the Mini Wheelbot - is engineered for production in small fleet quantities to serve as a hardware test bed at DSME.
|[Contribution to a book, Contribution to a conference proceedings]|
State Estimation and Model-Predictive Control for Multi-Robot Handling and Tracking of AGV Motions using iGPS
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) / IROS 2021 Online ; IEEE, RSJ, IEEE MSIT Robotics & Automation Society, SICE, IES, NIF - New Technology Foundation, 1038-1045, 2021
|Storm, Christoph (Corresponding author)|
Hose, Henrik (Corresponding author)
Schmitt, Robert H. (Corresponding author)