Model-Aided INS With Sea Current Estimation for Robust Underwater Navigation

Hegrenæs, Øyvind; Hallingstad, Oddvar

doi:10.1109/joe.2010.2100470

Cited by 156 publications

(89 citation statements)

References 33 publications

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“…In Hegrenaes and Hallingstad (2011) (Hegrenaes and Berglund (2009)). The assumption is a time-varying current in the measured water sampling volume.…”

Section: Vehicle Model Based Navigationmentioning

confidence: 99%

Mid-water current aided localization for autonomous underwater vehicles

et al. 2016

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Survey-class Autonomous Underwater Vehicles (AUVs) typically rely on Doppler Velocity Logs (DVL) for precision localization near the seafloor. In cases where the seafloor depth is greater than the DVL bottom-lock range, localizing between the surface and the seafloor presents a localization problem since both GPS and DVL observations are unavailable in the midwater column. This work proposes a solution to this problem that exploits the fact that current profile layers of the water column are near constant over short time scales (in the scale of minutes). Using observations of these currents obtained with the Acoustic Doppler Current Profiler (ADCP) mode of the DVL during descent, along with data from other sensors, the method discussed herein constrains position error. The method is validated using field data from the Sirius AUV coupled with view-based Simultaneous Localization and Mapping (SLAM) and on descents up to 3km deep with the Sentry AUV.

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“…In Hegrenaes and Hallingstad (2011) (Hegrenaes and Berglund (2009)). The assumption is a time-varying current in the measured water sampling volume.…”

Section: Vehicle Model Based Navigationmentioning

confidence: 99%

Mid-water current aided localization for autonomous underwater vehicles

et al. 2016

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“…Finally, we compared the proposed MA-INS (denoted by INS+VDNM (optimized)) to the strategy proposed in [15] (denoted by INS+3-DOF NLDM). Both strategies are illustrated in Figure 20.…”

Section: Comparison To the Reported Ma-ins Strategymentioning

confidence: 99%

“…It should be noted that the difference between the two strategies is that the VDNM provides an estimate of the attitude of the system that is used in the correction process. Furthermore, for the proposed configuration, the VDNM constitutes the core of the observer, while in the alternative structure of [15] this role is played by the INS. Figure 21 and Table 6 summarize the comparative results of the two strategies.…”

Section: Comparison To the Reported Ma-ins Strategymentioning

confidence: 99%

Model-Aided Navigation with Sea Current Estimation for an Autonomous Underwater Vehicle

Martínez

Hernández

Sahli

et al. 2015

International Journal of Advanced Robotic Systems

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This paper presents a strategy to improve the navigation solution of the HRC-AUV by deploying a model-aided inertial navigation system (MA-INS). Based on a simpler three-DOF linear dynamic model (DM) of the vehicle, and implemented through a Kalman filter (KF), the performance of the proposed MA-INS is compared to state-of-theart solutions based on non-linear models. The model allows the online estimation of the sea current parameters before and during the navigation mission. Qualitative and quantitative evaluations as well as a statistical significance test are performed using both simulated and real data, demonstrating the usefulness of the proposed model-aided navigation.

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“…[1], while interesting state of the art navigation technologies for AUVs can be found in [16]. The recent paper [8] reports the state of the art of model-aided inertial navigation system for underwater vehicles, while [10] describes a six degree of freedom AUV navigation approach with IMU, LBL, DVL. The paper [5] presents an approach, alternative to standard LBL triangulation techniques, for AUV localization within a field of surface floating buoys; the approach is based on a set-membership technique and considers unknown but bounded measurement errors.…”

Section: Related Workmentioning

confidence: 99%

Opportunistic localization of underwater robots using drifters and boats

Arrichiello

Heidarsson

Sukhatme

2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-The paper characterizes the performance of Autonomous Underwater Vehicle (AUV) localization when the AUV moves in environments where floating drifters or surface vessels are present and can be used for relative localization. In particular, we study how localization performance is affected by parameters e.g. surface object density, their visibility range and their motion. We present a discrete-time nonlinear model for an AUV equipped with onboard sensors and relative positioning information from surface objects (e.g., ranging and bearing) and derive the associated relative Posterior Cramér-Rao Lower Bound. We introduce a probabilistic motion model for the AUV, based on a random direction mobility model, to analyze the expected performance of the localization algorithm in terms of hitting time between the AUV and the surface objects. Finally, an extensive simulation analysis is performed using a discrete time Extended Kalman Filter with Maximum-Likelihood Data Association. As a proof of concept, an AUV equipped with an upward looking sonar is shown to detect a surface vessel and improve its localization estimate.

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Model-Aided INS With Sea Current Estimation for Robust Underwater Navigation

Cited by 156 publications

References 33 publications

Mid-water current aided localization for autonomous underwater vehicles

Mid-water current aided localization for autonomous underwater vehicles

Model-Aided Navigation with Sea Current Estimation for an Autonomous Underwater Vehicle

Opportunistic localization of underwater robots using drifters and boats

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