AI-Driven Cognitive Robotic Platform for Agile Production environments.
Programme: H2020-ICT-46-2020
Duration: January 2021– December 2024
Partners: BFH (BERNER FACHHOCHSCHULE), BIBA (BREMER INSTITUT FUER PRODUKTION UND LOGISTIK), MR. NEC, FUNDACIÓN AITIIP, UNIVERSIDAD DE DEUSTO, POLE EMC2, CABKA GROUP, IKOR SISTEMAS ELECTRONICOS, SIGMA CLERMONT, IMR (IRISH MANUFACTURING RESEARCH), NUTAI (NUEVAS TÉCNICAS DE AUTOMATIZACIÓN INDUSTRIAL), STERIPACK, STAM SRL, ICPE, VIC (VICOMTECH), MOSES PRODUCTOS, PRIZZTECH.
Webpage: https://acrobaproject.eu/
Más información:
As modern industrial robotic systems become smarter and more flexible, they are rather tailored for specific, large scale applications, making its implementation too complex and costly for smaller operators. The ACROBA project aims to develop and demonstrate a novel concept of cognitive robotic platforms based on a modular approach able to be smoothly adapted to virtually any industrial scenario applying agile manufacturing principles.
A novel ecosystem will be built as a result of this project, enabling the fast and economic deployment of advanced robotic solutions in agile manufacturing industrial lines, especially industrial SMEs The novel industrial platform will take advantage of artificial intelligence and cognitive modules to meet personalisation requirements and enhance mass product customisation through advanced robotic systems capable of self-adapting to the different production needs. The platform will depart from the COPRA-AP reference architecture for the design of a novel generic module-based platform easily configurable and adaptable to virtually any manufacturing line. This platform will be provided with a decentralized ROS node-based structure to enhance its modularity.
ACROBA Platform will definitely serve as a cost-effective solution for a wide range of Industrial sectors, both inside the consortium as well as additional industrial sectors that will be addressed in the future.
The ACROBA project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017284. |