Scientific coordinator:

Partners:
Fundacio Eurecat (ES)
Alstom Transporte SA (ES)
Nissan Motor Iberica SA (ES)
CNR-STIIMA (IT)
STAM srl (IT)
CEMBRE S.p.A. (IT)
MCM S.p.A. (IT)
Fraunhofer IWU (DE)
RWTH Aachen University (DE)
Technische Universität Darmstadt (DE)
Goizper S. Coop (ES)
Strane Innovation Sas (FR)
Laboratory for Manufacturing Systems & Automation (EL)
Intrasoft International SA (LU)
UNE- Spanish Association for Standardization (ES)

Type: H2020

End date: 2022

Start date: 2018

Duration: 48

Overall budget: € 7.351.467,50

Funding: € 7.351.467,50

CNR cost: € 605.875,00

CNR funding: € 605.875,00

STIIMA budget: € 331.578,58

STIIMA funding: € 331.578,58

Safe and effective HumAn-Robot coopEration toWards a better cOmpetiveness on cuRrent automation lacK manufacturing processes.

Sharework project endows an industrial work environment of the necessary “intelligence” and methods for the effective adoption of Human Robot Collaboration (HRC) with no fences.

The project develops a software and hardware modular system capable of understanding the environment and human actions through knowledge and sensors, future state predictions, smart data processing, augmented reality and gesture and speech recognition technology in order to make the robot overcome human barriers and ensure a more effective cooperation.

Sharework is applied in four types of real industrial scenarios in the automotive, railway, metal and capital goods manufacturing industries. Sharework solution will be able to apply to other relevant industrial environments and different industrial assembly and production processes, improving the efficiency of manufacturing processes and guaranteeing the safety of the worker.

Scientific and technological, as well as industrial excellence, are represented by the consortium, which comprises 15 partners located in six different countries in Europe. The project started on November, 2018 and will last until October 2022. It has a total budget of 7.351 million euros funded by the European Union’s Horizon 2020 Research and Innovation Programme, under grant agreement No. 820807