Roboclette, the raclette robot


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Discover the Roboclette, the iconic robot that is the unmissable star of Workshop 4.0. As an emblematic symbol of Valaisan genius, the Roboclette is the first machine in the world capable of scraping raclette cheese. This incredible innovation was born from the collaboration between Emmanuel Pignat, Sylvain Calinon and Nicolas Fontaine, and came to life thanks to the development carried out at the Idiap Research Institute. The dazzling success of the Roboclette was made possible thanks to the contribution of Eddy Baillifard, Valais/Wallis Promotion and Workshop 4.0. This technological gem demonstrates the full potential of robotics and artificial intelligence research in Valais, combining both tradition and innovation.

Request a quote to host Roboclette at your event

Request a quote now for the privilege of hosting the scraper robot at your next event. Our complete service includes:

  • Transportation and installation of the robot
  • Presence of a technician on site
  • 3 Valdor AOP raclette cheeses
  • Hugo Reitzel Pickles and Onions

Contact us now to get your personalized offer.

When a robot learns to make traditional Swiss raclette thanks to AI

The combination of the know-how of master cheesemaker Eddy Baillifard, founder of Raclett'House, and the expertise of the Robot Learning & Interaction group of the Idiap Research Institute has made it possible to create the first raclette prepared by a robot . Beyond the technical challenge, this project highlights the potential of demonstration learning techniques and human-robot collaboration.

The first raclette made by a robot

The collaboration between Eddy Baillifard and the Robot Learning & Interaction group has resulted in an extraordinary achievement: the first raclette prepared by a robot. This project required a combination of cheesemaking and robotics skills to accurately reproduce the characteristic gesture of raclette. Emmanuel Pignat, a doctoral student in Idiap's robotics group, developed an innovative approach. By guiding the robot's arm, Eddy Baillifard allowed the robot to record the movements and forces required to scrape the melted cheese. Thanks to this demonstration-based learning technique, the robot was able to gradually acquire the skills needed to make raclette autonomously.

When tradition and innovation meet

The production of raclette by a robot using AI and learning by demonstration is the result of a collaboration supported by the canton of Valais. Which recognizes the importance of scientific research in the development of new technologies. The canton of Valais provided financial support for this innovative scientific research. The local authorities understood the importance of this collaboration between master cheesemaker Eddy Baillifard, the Robot Learning & Interaction group of the Idiap Research Institute and other key players. This financial support made it possible to put in place the necessary resources to carry out the project.

The creation of a specific oven by the TTM company

In order for the robot to be able to pick up the plate with the melted cheese, close collaboration with the company TTM was necessary. TTM created a specific oven with a handle adapted to facilitate the robot's handling of the plate.

Facilitating contacts by Nicolas Fontaine

Nicolas Fontaine, a young local entrepreneur, played a key role in facilitating contacts between TTM, Raclett'House and Valais/Wallis Promotion. His knowledge of the local economic fabric and his commitment to innovation helped create synergy between the different stakeholders in the project.

The Future of Human-Robot Collaboration

The making of raclette by a robot is just one example of the potential offered by the collaboration between man and machine. Continued advances in the field of AI and robotics open the way to new applications and new opportunities for collaboration.

How does it work?

  • Demonstration learning offers an intuitive approach to reprogramming robots.
  • The robot records positions, orientations, speeds and accelerations which are taught through several demonstrations.
  • He can then use these variations to adapt his movements to new situations.
  • A sensor measures the force applied to allow the robot to adapt its gesture. Here, the robot has learned that it must apply a precise force rather than a movement at a precise height, while maintaining a constant speed to execute the movement.