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


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


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


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


Increase in job quality index


Reduction in programming time/cost


Reduction in reconfiguration time/cost
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Check out our video where we show how does a user demonstrate a liquid pouring task to the #robot. The robot is then required to execute the same task but on a different plane with different initial and goal positions and orientations ๐Ÿค–๐Ÿ‘‡ https://youtu.be/VgjZB3wVQ1c via @YouTube

๐Ÿค” Did you know that during riveting, the pneumatic hammer experiences accelerations up to 1000 higher than the gravitational acceleration?๐Ÿ™‚This is the basis for our development of an industrial #robotic system that can perform assembly operations, in collaboration with a human.

This mobile application, developed by @Idiap_ch allows any non-expert user to control the #robot, teach movements to perform tasks, as well as visualize trajectories before even executing on the real robot ๐Ÿค–๐Ÿ‘จโ€๐Ÿญ

What do you think about this app? Would you use it?

#Robotics #HRC

This project has received funding from the European Unionโ€™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
Collaborate Project CoLLaboratE Project
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