Robots need to learn to localize themselves and what is happening in their surroundings. This will enable them to operate more accurately and work together. SAM XL is developing a manufacturing testbed for post-production quality inspection, in combination with mobile manipulators.
Autonomous robots do not fully understand their open environments, their complex missions, their intricate realizations, and the unexpected events that affect their performance. This is a subject that artificial intelligence approaches based on machine learning are not addressing well. Therefore, an improvement in the capability to understand of autonomous robots is needed. This project tries to provide a solution to this need in the form of:
This will lead to increasing the resilience of drone teams, improving flexibility of manufacturing robots, and augment human alignment of social robots.
The project has three development threads – theory, technology, application – with three associated objectives related to project products, and one impact thread with an objective related to the robot software community. The four threads are:
SAM XL is active in the application thread and will develop a manufacturing testbed for the quality inspection of the manufacturing of large parts combined with mobile manipulators. Robotic technologies inserted in manufacturing cells will address the problem of flexible adaptation to changing production conditions relating to the locations of the robot, the tools needed, the need of learning new operations or the unexpected events related to finding defects in manufactured parts.
Find more information at https://coresense.eu/
The Coresense project is funded by the EC Horizon Europe programme though grant HE #101070254 inside the HORIZON-CL4-2021-DIGITAL-EMERGING-01-11 topic.
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