Jun 1 – 5, 2026
Hotel Hermitage
Europe/Rome timezone
ZOOM Connection: ID number: 889 8241 9552 | Access Code: 150555

Session

DRD8 Session 4

Jun 5, 2026, 8:30 AM
Maria Luisa (Hotel Hermitage)

Maria Luisa

Hotel Hermitage

57037 Portoferraio (LI) Isola d’Elba Italy https://www.hotelhermitage.it/en/home

Conveners

DRD8 Session 4

  • Diego Alvarez Feito (CERN)
  • Corrado Gargiulo (CERN)

Presentation materials

There are no materials yet.

  1. Corrado Gargiulo (CERN), Diego Alvarez Feito (CERN)
    6/5/26, 8:30 AM
  2. Haoyu Shi (Chinese Academy of Sciences (CN))
    6/5/26, 8:40 AM

    Real-time, high-precision radiation dose monitoring and environmental parameter measurement of key components within the experimental halls of high-energy particle colliders are essential for ensuring equipment safety and experimental data integrity. Conventional manual measurement methods not only face significant personnel safety risks and operational inefficiencies in high-radiation areas...

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  3. Paolo Francesco Scaramuzzino
    6/5/26, 9:00 AM

    Remote inspection of underground infrastructure at CERN increasingly relies on mobile robotic systems to reduce human exposure to hazardous environments and improve operational efficiency. These environments, including detector caverns and accelerator tunnels, present significant challenges for wireless communication due to their complex geometry, confined spaces, and the presence of large...

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  4. Carolin Benjamins (RWTH Aachen)
    6/5/26, 9:20 AM

    The development of next-generation tracking detectors comprises challenges in mechanical integration, high-density service routing, and long-term maintenance. As these systems become more complex and are deployed in constrained, high-radiation environments, traditional manual intervention reaches its limit.

    di.monta introduces a novel approach to detector lifecycle management through...

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  5. Carolin Benjamins (RWTH Aachen)
    6/5/26, 9:40 AM

    The disassembly of complex technical systems is still predominantly performed manually, as the required process knowledge—such as action sequences, grasping positions, and handling strategies—is difficult to formalize and implement. Observing human workers during task execution offers a promising approach to automatically extract this knowledge. This is particularly relevant in domains such as...

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  6. Burkhard Schmidt (CERN)
    6/5/26, 10:00 AM

    Feedback from recent DRD Managers Forum Meetings

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  7. Fabrizio Palla
    6/5/26, 10:20 AM
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