The production of Fiber-Reinforced Plastics (FRP) usually requires a lot of expert knowledge possessed by individual workers. However, a growing shortage of skilled workers prevails. In addition, high quality demands are placed on production. One possible solution for these requirements could be robot-based automation and human-robot collaboration within the process.
In this thesis, you will create a framework for the execution of the Preforming step of FRP production using a robot arm. The thesis contribution is two fold; first a data-driven model is needed to estimate the forces needed throughout the process. After that, you apply the model for trajectory generation given a 3D model of the product.
- Willingness to learn
- Solid Pyhton knowledge
- Knowledge of machine learning
- Experience with a machine learning framework is a plus
- Knowledge of ROS and experience with one or more robot platforms are a plus
If you are interested in it or have questions, please feel free to contact Mohamed Behery or Hannah Dammers (ITA) via email: