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Adaptive Radiation Survey Using an Autonomous Robot Executing LiDAR Scans in the Large Hadron Collider

  • Conference paper
  • First Online:
Robotics Research (ISRR 2022)
  • The original version of the chapter has been revised. The following author’s family name “Alejandro Díaz Rosales; Jorge Playán Garai; Carlos Veiga Almagro” has been changed to “A. Díaz Rosales; J. Playán Garai; C. Veiga Almagro”. A correction to this chapter can be found at https://doi.org/10.1007/978-3-031-25555-7_38

Abstract

At CERN, radiation surveys of equipment and beam lines are important for safety and analysis throughout the accelerator complex. Radiation measurements are highly dependent on the distance between the sensor and the radiation source. If this distance can be accurately established, the measurements can be used to better understand the radiation levels of the components and can be used for calibration purposes. When surveys are undertaken by the Train Inspection Monorail (TIM) robot, the sensor is at a constant distance from the rail, which means that it is at a known distance and height from the centre of the beam line. However, the distance of the sensor to the closest surface of the beam line varies according to what kind of equipment is installed on the beam line at this point. Ideally, a robotic survey would be completed with online adaption of the sensor position according to the equipment present in the LHC. This new approach establishes a scan of the surface with a 2D LiDAR while moving along the tunnel axis in order to obtain a 3D scan of the environment. This 3D scan will be used to generate online trajectories that will allow the robot to accurately follow the beam line and thus measure the radiation levels.

H. Gamper, D. Forkel, A. D. Rosales and J. P. Garai—Equal contribution of authors.

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Change history

  • 21 July 2024

    A correction has been published.

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Correspondence to Hannes Gamper .

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Gamper, H. et al. (2023). Adaptive Radiation Survey Using an Autonomous Robot Executing LiDAR Scans in the Large Hadron Collider. In: Billard, A., Asfour, T., Khatib, O. (eds) Robotics Research. ISRR 2022. Springer Proceedings in Advanced Robotics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-031-25555-7_20

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