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
Latest News
Twitter Feed

Do you think you need lots of programming skills to train #CollaborativeRobots? No, you don't! We are developing technologies that enable users to intuitively teach robots the various tasks. No training is required as the #robot tasks will be optimized during the exploitation! ๐Ÿค–

To improve adaptation and safety in industrial #robotic tasks,@Idiap_ch is developing robust and adaptive behaviors.

Thanks to #BayesianLearning, these behaviors will allow the #robot to execute either a weighted combination of behaviors or the most probable one.


Check out this Open Access Book on #Industry40 that reflects recent R&I results from #H2020 projects and covers multiple #digitalautomation topics including data-driven #cognitivecomputing and #collaborativerobotic solutions in #factoriesofthefuture ๐Ÿ‘‡โš™

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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