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Comparison of Kalman and Interval Approaches for the Simultaneous Localization and Mapping of an Underwater Vehicle

Jérémy Nicola 1 Luc Jaulin 2
2 Lab-STICC_ENSTAB_CID_PRASYS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : In this paper we compare the use of a Kalman filter and a Robust State Observer for the localization and mapping of an underwater vehicle using range-only measurements between the vehicle and a set of beacons lying on the seafloor. As expected, we show that the Kalman filter performs great when we have a reasonably good prior information on the location of the vehicle and the beacons. Based on set-membership methods, the Robust State Observer demonstrates an outstanding capacity to provide consistent estimates (where the true solution is in the estimated confidence domain) in the presence of outliers at the cost of a very coarse precision. The source of this lack of precision will be discussed.
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https://hal-ensta-bretagne.archives-ouvertes.fr/hal-01707402
Contributeur : Marie Briec <>
Soumis le : lundi 12 février 2018 - 17:41:15
Dernière modification le : mercredi 5 août 2020 - 03:50:30

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Jérémy Nicola, Luc Jaulin. Comparison of Kalman and Interval Approaches for the Simultaneous Localization and Mapping of an Underwater Vehicle. Luc Jaulin. Marine Robotics and Applications, Springer, pp.117-136, 2018, 978-3-319-70723-5. ⟨10.1007/978-3-319-70724-2_8⟩. ⟨hal-01707402⟩

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