Stammdaten

Titel: CNS Flight Stack for Reproducible, Customizable, and Fully Autonomous Applications
Untertitel:
Kurzfassung:

While low-level auto pilot stacks for aerial vehicles focus on robust control, sensing, and estimation, the continuous advancement of higher-level autonomy for aerial vehicles requires much more complex higher-level flight stacks in order to enable safe, fully autonomous long-duration missions. Rather than focusing on the low-level control, high-level flight stacks are required to monitor the system's integrity continuously, initiate contingency plans, execute mission plans and adapt them in non-nominal situations, allow for proper data logging, and provide standardized interfaces and integrity verification for external mission planners and localization modules. To that end, we present our freely available, high-level flight stack (dubbed CNS Flight Stack) that meets the above requirements and at the same time a) is platform-agnostic through a generalized (embedded) hardware abstraction layer, b) uses low compute complexity for online use on embedded hardware, and c) can be extended with other sensor modalities, integrity checks, and mission modules. These additional properties make it reproducible on a variety of different platforms for safe and fully autonomous applications. We tested the proposed flight stack in over 450 real-world flights and report the failure modes our framework detected and also mitigated to avoid crashes of the aerial system.

Schlagworte: Software Architecture for Robotic and Automation, Autonomous Vehicle Navigation, Aerial Systems: Perception and Autonomy
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Erscheinungsdatum: 03.08.2022 (Online)
Erschienen in: IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters
zur Publikation
 ( IEEE; )
Titel der Serie: -
Bandnummer: 7
Heftnummer: 4
Erstveröffentlichung: Ja
Version: -
Seite: S. 11283 - 11290

Versionen

Keine Version vorhanden
Erscheinungsdatum: 03.08.2022
ISBN (e-book): -
eISSN: 2377-3766
DOI: http://dx.doi.org/10.1109/LRA.2022.3196117
Homepage: https://ieeexplore.ieee.org/document/9849131
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Intelligente Systemtechnologien
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Österreich
   hubert.zangl@aau.at
http://www.uni-klu.ac.at/tewi/ict/sst/index.html
zur Organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 202034 - Regelungstechnik
  • 202035 - Robotik
  • 207409 - Navigationssysteme
Forschungscluster
  • Selbstorganisierende Systeme
Zitationsindex
  • Science Citation Index Expanded (SCI Expanded)
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Control of Networked Systems

Kooperationen

Organisation Adresse
Aperture Robotics
93103 Santa Barbara, CA
Vereinigte St. v. Amerika
US - 93103  Santa Barbara, CA

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