Flexible and easily reconfigurable robotic workstation
Key problem
Nowadays the market is oriented towards a strong customization of products. This implies a shift of paradigm from mass production lines to flexible workstations that can be easily reconfigured to accommodate for the different needs.
Our objective
In this use case we aim at investigating the feasibility of applying teaching and learning algorithms to collaborative robots to enhance the flexibility of the workstation and simplify its programming.
The abilities to achieve
Key ability smart programming
Introduce intuitive interfaces for programming cobots in a more natural way
Key ability Autonomy
Autonomous manipulation of objects with different physical properties and sizes
Key ability Learning
Autonomous execution after a single demonstration
