Mission analysis, dynamics and robust control of an indoor blimp in a CERN detector magnetic environment.
CERN particle detectors
aerial inspection and mapping
harsh environment
indoor blimp
magnetic disturbances
robotic systems
robust control techniques
unmanned aerial vehicle
Journal
Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350
Informations de publication
Date de publication:
2023
2023
Historique:
received:
10
06
2023
accepted:
02
10
2023
medline:
30
10
2023
pubmed:
30
10
2023
entrez:
30
10
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37901165
doi: 10.3389/frobt.2023.1238081
pii: 1238081
pmc: PMC10611505
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1238081Informations de copyright
Copyright © 2023 Mazzei, Teofili, Curti and Gargiulo.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Références
Sci Robot. 2017 Jun 28;2(7):
pubmed: 33157901