Scientific Computing and Algorithmics Lab
We develop customized solutions for complex and computationally intensive problems ranging from nonlinear optimal control, multi sensor fusion, simulation and optimization of sensors to more general machine learning applications. Besides refined mathematical/physical modeling we put special emphasis on developing robust, efficient and ready to use implementations of our solutions.
Fields of activity
- Modeling and simulation in sensor development
- Optimal control and planning in robotics
- Machine Learning, Data Fusion and Bayesian Models
Selected projects
The links below lead to selected project examples. You can find additional information on the page Projects.