A fault diagnosis framework for MAVLink-enabled UAVs using structural analysis

Georgios Zogopoulos-Papaliakos, Michalis Logothetis, Kostas J. Kyriakopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

MAVLink is a popular message protocol for small Unmanned Aerial Vehicles (UAVs). In this work, we present a Fault Detection and Isolation (FDI) framework for fixed-wing UAVs which takes advantage of the information conveyed in MAVLink telemetry streams and produces a bank of residual generators. Structural Analysis is employed to systematically handle the varying set of available measurements, identify the observable faults and adjust the FDI system accordingly. Structural detectability and isolability analyses are carried out. A case-study on a real-life telemetry log of a UAV crash demonstrates the efficacy of the proposed approach.

Original languageEnglish (US)
Title of host publication2019 International Conference on Robotics and Automation, ICRA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages676-682
Number of pages7
ISBN (Electronic)9781538660263
DOIs
StatePublished - May 2019
Event2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada
Duration: May 20 2019May 24 2019

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2019-May
ISSN (Print)1050-4729

Conference

Conference2019 International Conference on Robotics and Automation, ICRA 2019
Country/TerritoryCanada
CityMontreal
Period5/20/195/24/19

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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