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Ambition

Revolutionize the way industrial robots learn to cooperate with human workers for performing assembly tasks.

Excellence

Equip robots with collaborative skills, using deep reinforcement learning algorithms and safety strategies.

Consortium

14 partners form the CoLLaboratE project, including universities, research institutes, SMEs and industries.

Impact

The excpected impact is to improve efficiency and flexibility by automatic assembly systems capable to rapidly learn new tasks

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Increase in job quality index

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Reduction in programming time/cost

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Reduction in reconfiguration time/cost
Latest News
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Twitter Feed

The CfP for our workshop hosted by @icvs on movement analytics and gesture recognition when collaborating with machines in Industry4.0 is now open!
#robotics #HAI #gestures #workers #Industry4_0
@collaborate_eu @MINES_ParisTech @psl_univ @_ARMINES_ https://t.co/j9MgCxkSlu

The CoLLaboratE informative #brochure is now available on our website! @EU_H2020 @FOF
https://t.co/vzopBBMzDW

Can you give us your feedback on human-robot collaboration? Please take 10' to answer some questions about collaborative robots in industrial assembly tasks and become part of @collaborate_eu
@EU_H2020 @FoF_EU
➡️https://t.co/KmC1DpBgXc⬅️



This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820767.

The website reflects only the view of the author(s) and the Commission is not responsible for any use that may be made of the information it contains.

Contact Information
Prof. Zoe Doulgeri
Automation & Robotics Lab
Aristotle University of Thessaloniki
Department of Electrical & Computer Engineering
Thessaloniki 54124, Greece
info(at)collaborate-project(dot)eu
Collaborate Project CoLLaboratE Project
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