AWAKE is a proton-driven plasma wakefield acceleration experiment. We show that the experimental setup briefly described here is ready for systematic study of the seeded self-modulation of the 400 GeV proton bunch in the 10 m-long rubidium plasma with density adjustable from 1 to 10×10 14 cm −3 . We show that the short laser pulse used for ionization of the rubidium vapor propagates all the way along the column, suggesting full ionization of the vapor. We show that ionization occurs along the proton bunch, at the laser time and that the plasma that follows affects the proton bunch.

Robotic interventions with redundant mobile manipulators pose a challenge for telerobotics in hazardous environments, such as underwater, underground, nuclear facilities, particle accelerators, aerial or space. Communication issues can lead to critical consequences, such as imprecise manipulation resulting in collisions, breakdowns and mission failures. The research presented in this paper was driven by the needs of a real robotic intervention scenario in the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN). The goal of the work was to develop a framework for network optimisation in order to help facilitate Mixed Reality techniques such as 3D collision detection and avoidance, trajectories planning, real-time control, and automatized target approach. The teleoperator was provided with immersive interactions while preserving precise positioning of the robot. These techniques had to be adapted to delays, bandwidth limitation and their volatility in the 4G shared network of the real underground particle accelerator environment. The novel application-layer congestion control with automatic settings was applied for video and point cloud feedback. Twelve automatic setting modes were proposed with algorithms based on the camera frame rate, resolution, point cloud subsampling, network round-trip time and throughput to bandwidth ratio. Each mode was thoroughly characterized to present its specific use-case scenarios and the improvements it brings to the adaptive camera feedback control in teleoperation. Finally, the framework was presented according to which designers can optimize their Human-Robot Interfaces and sensor feedback depending on the network characteristics and task.

No abstract

In hazardous environments, where conditions present risks for humans, the maintenance and interventions are often done with teleoperated remote systems or mobile robotic manipulators to avoid human exposure to dangers. The increasing need for safe and efficient teleoperation requires advanced environmental awareness and collision avoidance. The up-to-date screen-based 2D or 3D interfaces do not fully allow the operator to immerse in the controlled scenario. This problem can be addressed with the emerging Mixed Reality (MR) technologies with Head-Mounted Devices (HMDs) that offer stereoscopic immersion and interaction with virtual objects. Such human-robot interfaces have not yet been demonstrated in telerobotic interventions in particle physics accelerators. Moreover, robotic operations often require a few experts to collaborate, which increases the system complexity and requires sharing a multi-user Augmented Reality (AR) workspace. The multi-user telerobotics with shared control in the AR has not yet been approached in the industrial state-of-the-art. In this work, the developed MR human-robot interface using the AR HMD is presented. The interface adapts to the constrained wireless networks in particle accelerator facilities and provides reliable high-precision interaction and specialized visualization. The multimodal operation uses hands, eyes and user motion tracking, and voice recognition for control, as well as offers video, 3D point cloud and audio feedback from the robot. Multiple experts can collaborate in the AR workspace locally or remotely, share the robot's control and monitor robotic teleoperation. Ten (10) operators tested the interface in intervention scenarios in the European Organization for Nuclear Research (CERN) with complete network characterization and measurements to conclude if operational requirements were met and if the network architecture could support single and multi-user communication load.The interface system has proved to be operationally ready at the Technical Readiness Level (TRL) 8 -and was validated through successful tests and demonstration in single and multi-user missions. Some areas of system limitations and further work were identified, such as optimising the network architecture for multi-user scenarios or high-level interface actions applying automatic interaction strategies with the robot depending on network conditions.