Phygital Robotics Education Platform for Industrial Upskilling

Phygital Robotics Education Platform for Industrial Upskilling

Participants:

The progression of the cobotics market for industrial applications requires dedicated teaching programs to upskill the employees and to form new personnel. Current training programs either requires centralized sessions, shared hardware, and/or instructor-led demonstrations. Simulators exist, but they are usually disconnected from real-world setups and offer limited feedback, realism, or transferability. This fragmented pipeline slows down learning, increases costs, and excludes many companies (especially SMEs) from building in-house automation skills.

The goal of this project is to develop and validate a robotics training system that combines immersive, browser-based simulation with guided physical robot interaction. It aims to lay the groundwork for a distributed, scalable and phygital (physical + digital) robotics training model, by lowering access barriers and positioning Switzerland as a leader in future-ready, modular workforce transformation.

Research Partner :

Idiap research institute

Founded in 1991, Idiap is an independent, nonprofit research foundation based in Martigny. It is affiliated with the Ecole Polytechnique Fédérale de Lausanne (EPFL) and is one of the most active independent research institutions in information technology. Idiap has a long history of contributions in AI. The Robot Learning & Interaction group, created in 2014 and headed by Dr. Sylvain Calinon, is expert in combining learning and optimization approaches to facilitate the transfer of manipulation skills to robots.


Implementation partner:

Swiss Cobotics Competence Center S3C

Founded in 2022 in Biel/Bienne, Switzerland, is a non-profit technology transfer center for collaborative robotics technologies. The center promotes industry and academia collaborations for advancing the state-of-the-art in human-robot collaboration by offering extensive testing and training services. Its expertise spans robot learning from demonstration, force-based skill learning, and the development of user-centered, interactive systems for robot programming.

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