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Eloise Matheson
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4 records found
1
Conference paper
(2025)
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Eloise Matheson, Luca Rosario Buonocore, Sergio Di Giovannantonio, Gianluca D'Antuono, Enrico Romagnoli, Carlos Veiga Almagro, Álvaro García González, Giancarlo D'Ago, Alejandro Díaz Rosales, More authors...
Robots are useful tools for performing tasks in hazardous environments to increase personnel safety and infrastructure availability. At CERN, they are used for inspection, maintenance and repair tasks including equipment autopsies. This paper details the robot fleet (hardware, software and user interfaces) and the main interventions undertaken in 2024 to showcase robot capabilities and open challenge areas.
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Robots are useful tools for performing tasks in hazardous environments to increase personnel safety and infrastructure availability. At CERN, they are used for inspection, maintenance and repair tasks including equipment autopsies. This paper details the robot fleet (hardware, software and user interfaces) and the main interventions undertaken in 2024 to showcase robot capabilities and open challenge areas.
Conference paper
(2025)
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Eloise Matheson, Alejandro Diaz Rosales, Jorge Playan Garai, Carlos Veiga Almagro, Hugo Perier, Francesco Riccardi, Luca Rosario Buonocore, Mario Di Castro
Robotic interventions in hazardous environments augment or replace dangerous work carried out by humans, and this is especially true in areas where radiation is present. These missions must be carefully designed, prepared, implemented, and analyzed in order to optimize human-robot collective performance and minimize the dangers posed to machines, operators, and support personnel. This paper describes the case study of over 200 hours of use of a redundant manipulator mounted on a movable robot in operation inside the Large Hadron Collider at CERN to validate beam loss monitor sensors using a radioactive source.
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Robotic interventions in hazardous environments augment or replace dangerous work carried out by humans, and this is especially true in areas where radiation is present. These missions must be carefully designed, prepared, implemented, and analyzed in order to optimize human-robot collective performance and minimize the dangers posed to machines, operators, and support personnel. This paper describes the case study of over 200 hours of use of a redundant manipulator mounted on a movable robot in operation inside the Large Hadron Collider at CERN to validate beam loss monitor sensors using a radioactive source.
Conference paper
(2024)
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A. Díaz Rosales, Jose Rodriguez-Nogueira, Eloise Matheson, D.A. Abbink, L. Peternel
Teleoperation is a crucial technology enabling human operators to control robots remotely to perform tasks in hazardous and difficult-to-access environments. Tasks in such environments often involve complex physical interactions with tools and objects of various softness. To this end, teleimpedance enables the operators to adjust the robot impedance in real-time to simplify such interactions. While the existing teleimpedance approaches provide several interfaces to command the robot impedance, there are no interfaces to visualize both the commanded impedance and that of the objects to be interacted with. This paper presents a novel interface to provide visual feedback on the impedance of remote robots and objects. To do so, we use virtual stiffness ellipsoids and different modes that display the individual impedance of the robot and objects as well as combined post-contact impedance. The key advantage of visual feedback on the impedance compared to force feedback is that the operator can see the interaction characteristics before the contact occurs. This enables the operator to act proactively before contact rather than just reactively after the contact. This paper also proposes a new intuitive way to command the robot impedance using mixed reality, interacting with these ellipsoids and modifying them as needed. To demonstrate the key functionalities of the developed interface, we performed proof-of-concept experiments on teleoperated tasks.
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Teleoperation is a crucial technology enabling human operators to control robots remotely to perform tasks in hazardous and difficult-to-access environments. Tasks in such environments often involve complex physical interactions with tools and objects of various softness. To this end, teleimpedance enables the operators to adjust the robot impedance in real-time to simplify such interactions. While the existing teleimpedance approaches provide several interfaces to command the robot impedance, there are no interfaces to visualize both the commanded impedance and that of the objects to be interacted with. This paper presents a novel interface to provide visual feedback on the impedance of remote robots and objects. To do so, we use virtual stiffness ellipsoids and different modes that display the individual impedance of the robot and objects as well as combined post-contact impedance. The key advantage of visual feedback on the impedance compared to force feedback is that the operator can see the interaction characteristics before the contact occurs. This enables the operator to act proactively before contact rather than just reactively after the contact. This paper also proposes a new intuitive way to command the robot impedance using mixed reality, interacting with these ellipsoids and modifying them as needed. To demonstrate the key functionalities of the developed interface, we performed proof-of-concept experiments on teleoperated tasks.
Conference paper
(2023)
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Hannes Gamper, David Forkel, Alejandro Díaz Rosales, Jorge Playán Garai, Carlos Veiga Almagro, Luca Rosario Buonocore, Eloise Matheson, Mario Di Castro
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.
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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.