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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
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🤖 @CERTHellas developed a module with which the collaborative #robot by using RGBD cameras can detect and track its human coworker in real-time. The #cobot can also avoid humans by using a module developed by @Aristoteleio to perform the task with safety and efficiency!

Using visual demonstration, we can teach the #robot how to perform a TV assembly in collaboration with a human coworker👨‍🏭The #CollaborativeRobot 🤖 analyses the video in order to understand the performed actions and object relations👇

@CERTHellas #Cobots #HorizonEU #H2020 #Robot

Check out this backstage video from one of our use cases to see how does the #robot support the riveting process by holding the bucking bar. In CoLLaboratE, we aim to enable #robots to safely and effectively perform assembly operations, in collaboration with a human operator🤖👨‍🏭



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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