A Fault Diagnosis Framework for MAVLink-Enabled UAVs Using Structural Analysis

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

ICRA 2019poster4 citations

A Fault Diagnosis Framework for MAVLink-Enabled UAVs Using Structural Analysis

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

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.

BibTeX

@inproceedings{icra2019_afaultdiagnosisf,
  title = {A Fault Diagnosis Framework for MAVLink-Enabled UAVs Using Structural Analysis},
  author = {Georgios Zogopoulos-Papaliakos and Michalis Logothetis and Kostas J. Kyriakopoulos},
  booktitle = {ICRA 2019},
  year = {2019}
}