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Article Dans Une Revue Algorithms Année : 2022

Experimental Validation of Ellipsoidal Techniques for State Estimation in Marine Applications

Andreas Rauh
Yohann Gourret
  • Fonction : Auteur
  • PersonId : 1142066
Katell Lagattu
Bernardo Hummes
Johannes Reuter
  • Fonction : Auteur
  • PersonId : 1142067
Stefan Wirtensohn
Patrick Hoher
  • Fonction : Auteur
  • PersonId : 1142068

Résumé

A reliable quantification of the worst-case influence of model uncertainty and external disturbances is crucial for the localization of vessels in marine applications. This is especially true if uncertain GPS-based position measurements are used to update predicted vessel locations that are obtained from the evaluation of a ship's state equation. To reflect real-life working conditions, these state equations need to account for uncertainty in the system model, such as imperfect actuation and external disturbances due to effects such as wind and currents. As an application scenario, the GPS-based localization of autonomous DDboat robots is considered in this paper. Using experimental data, the efficiency of an ellipsoidal approach, which exploits a bounded-error representation of disturbances and uncertainties, is demonstrated.
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Dates et versions

hal-03666881 , version 1 (12-05-2022)

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Andreas Rauh, Yohann Gourret, Katell Lagattu, Bernardo Hummes, Luc Jaulin, et al.. Experimental Validation of Ellipsoidal Techniques for State Estimation in Marine Applications. Algorithms, 2022, 15 (5), pp.162. ⟨10.3390/a15050162⟩. ⟨hal-03666881⟩
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