Mission analysis, dynamics and robust control of an indoor blimp in a CERN detector magnetic environment

Front Robot AI. 2023 Oct 13:10:1238081. doi: 10.3389/frobt.2023.1238081. eCollection 2023.

Abstract

At the European Organization for Nuclear Research (CERN), a Research and Development (R&D) program studies robotic systems for inspection and maintenance of the next-generation of particle detectors. The design and operation of these systems are affected by the detector's cavern harsh environment consisting of high magnetic fields and radiations. This work presents a feasibility study for aerial inspection and mapping around a CERN particle detector using a robotic Lighter-than-Air (LtA) Unmanned Aerial Vehicle (UAV), specifically a blimp. Firstly, mission scenarios and the detector environment are introduced; in this context a new empirical model is proposed for the estimation of magnetic disturbances resulting from the interaction of electromagnetic motors with the external magnetic field. Subsequently, the design of a reference blimp and the control system is presented, comparing different control techniques, namely, Computed Torque Control (CTC), Sliding Mode Control (SMC) and Nonsingular Terminal Sliding Mode Control (NTSMC). Finally, the results of trajectory tracking simulations are reported, considering both the uncertainties of the dynamic parameters and the estimated magnetic disturbances. This work demonstrates that the blimp successfully follows desired trajectory, navigating complex environments while maintaining stability and accuracy. Despite the challenges posed by high magnetic fields, indoor blimps can effectively offer safer and more efficient approaches to facility surveillance and maintenance, reducing radiation exposure for human personnel and minimizing detector downtime.

Keywords: CERN particle detectors; aerial inspection and mapping; harsh environment; indoor blimp; magnetic disturbances; robotic systems; robust control techniques; unmanned aerial vehicle.

Grants and funding

This research was funded through a collaboration between the European Organization for Nuclear Research (CERN) and the Automation Robotics and Control for Aerospace (ARCA) Laboratory, School of Aerospace Engineering, University of Rome La Sapienza. The CERN organization provided financial support for the research activities, including the payment of the research grant through the ARCA Lab. Furthermore, CERN covered the publication fees associated with the submission of the paper to the journal.