Control Design Optimisations of Robots for the Maintenance and Inspection of Particle Accelerators

Conference Paper (2023)
Author(s)

A. Díaz Rosales (TU Delft - Human-Robot Interaction, CERN)

Hannes Gamper (Johannes Kepler University Linz, CERN)

Mario Di Castro (CERN)

Research Group
Human-Robot Interaction
DOI related publication
https://doi.org/10.18429/JACoW-ICALEPCS2023-MO3AO07
More Info
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Publication Year
2023
Language
English
Research Group
Human-Robot Interaction
Pages (from-to)
153-159
ISBN (electronic)
978-3-95450-238-7
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Abstract

Automated maintenance and inspection systems have become increasingly important over the last decade for the availability of the accelerators at CERN. This is mainly due to improvements in robotic perception, control and cognition and especially because of the rapid advancement in artificial intelligence. The robotic service at CERN performed the first interventions in 2014 with robotic solutions from external companies. However, it soon became clear that a customized platform needed to be developed in order to satisfy the needs and in order to efficiently navigate through the cluttered, semi-structured environment. This led to the formation of a robotic fleet of about 20 different robotic systems that are currently active at CERN. In order to increase the efficiency and robustness of robotic platforms for future accelerators it is necessary to consider robotic interventions at the early design phase of such machines. Task specific solutions tailored to the specific needs can then be designed, which in general show higher efficiency than multipurpose industrial robotic systems. This paper presents current advances in the design and development of task specific robotic system for maintenance and inspection in particle accelerators, taking the 100 km long Future Circular Collider main tunnel as a use case. The requirements on such a robotic system, including the applied control strategies, are shown, as well as the optimization of the topology and geometry of the robotic system itself.