SOURCE-LINKED INTELLIGENCE

iMmersive leArninG for ImperfeCtion detectIon and repAir through human-robot interactioN

CORDIS · observation · Publication date unknown

ation, with the CR operating on the defects identified by the SR. The SR can also be used in connection with the welding robotic station in order to adapt the process parameters. The robots will use Artificial Intelligence modules to detect and discriminate the defects from multi-modal data (the SR) or to decide the best policy to use for defect rework (the CR). In both cases, the decision logic of the modules will be trained using machine learning algorithms. The training data set will be acquired with the help of workers, who will operate on semi-worked products within a controlled environment. The SR and the CR will rely on the software services of a common robotic platform. The solution will be developed adopting a human-centered approach, which will allow us to evaluate the impact of the innovation on the production processes and remove the most important asperities along this path. The effectiveness of the solution will be tested on a use-case, and its generality proven by recruiting additional contributors and use-cases through a FSTP scheme. Human-Robot Interaction, Machine

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recordType

award

status

SIGNED

region

EU

value

8332681.25

unit

EUR