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