Ziel
Traditional manufacturing systems lack the necessary flexibility and reconfigurability that can allow short production cycles and fast deployment of the updated system. Although the use of automation technologies based on industrial robots can increase the adaptability of a production line, the desired flexibility cannot be achieved until abilities for genuine collaboration of the robots with the human workers are developed. CoLLaboratE will revolutionize the way industrial robots learn to cooperate with human workers for performing new manufacturing tasks, with a special focus on the challenging area of assembly operations. The envisioned system for collaborative assembly will be capable of allocating human and robotic resources for executing the production plan sharing the tasks according to the capabilities of the available actors. The CoLLaboratE project will build upon state-of-the-art methods for teaching the robot assembly tasks using human demonstration, extending them to facilitate genuine human-robot collaboration. To this end, a framework for equipping the robots and AGV mobile platforms with basic collaboration skills, such as load sharing, human touch recognition and human intention detection, will also be developed, coupled with deep reinforcement learning algorithms for increasing adaptability. Special attention will be paid to providing effective safety strategies allowing the use of a fenceless approach within the production cell. As a result, closer collaboration will be achievable and efficient production plans making optimal use of the available resources will be designed and executed. The proposed solution will be evaluated in four different pilot sites, which will be implemented as collaborative factory floors of the industrial partners in Italy, Slovenia, Turkey, and Romania.
Wissenschaftliches Gebiet
CORDIS klassifiziert Projekte mit EuroSciVoc, einer mehrsprachigen Taxonomie der Wissenschaftsbereiche, durch einen halbautomatischen Prozess, der auf Verfahren der Verarbeitung natürlicher Sprache beruht.
CORDIS klassifiziert Projekte mit EuroSciVoc, einer mehrsprachigen Taxonomie der Wissenschaftsbereiche, durch einen halbautomatischen Prozess, der auf Verfahren der Verarbeitung natürlicher Sprache beruht.
Schlüsselbegriffe
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-NMBP-FOF-2018
Finanzierungsplan
RIA - Research and Innovation actionKoordinator
546 36 THESSALONIKI
Griechenland