A parallel hypothesis method of autonomous underwater vehicle navigation

LaPointe, Cara Elizabeth Grupe

doi:10.1575/1912/2853

Cited by 8 publications

(10 citation statements)

References 37 publications

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“…Larsen (2000b) developed an approach termed Synthetic LBL, which used measurements from a single acoustic transponder at an unknown location to constrain the error growth of a high performance INS system (Larsen 2000a). LaPointe (2009) developed techniques for using range measurements from a single transponder for deep sea positioning, extending the operating area beyond that of a typical LBL transponder network. Vaganay et al (2000) investigated techniques for homing to an acoustic beacon using only range measurements.…”

Section: ; Anmentioning

confidence: 99%

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Fallon

Παπαδόπουλος

Leonard

et al. 2010

The International Journal of Robotics Research

191

126

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This paper describes the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is provide a quantitative performance comparison of three estimators: particle filtering (PF), Nonlinear Least Squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.

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Section: ; Anmentioning

confidence: 99%

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Fallon

Παπαδόπουλος

Leonard

et al. 2010

The International Journal of Robotics Research

191

126

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“…Here we assume direct-path for simplicity. Multipath and parallel hypothesis [113] LBL measurement models are a topic of future research.…”

Section: Asynchronous Lbl Measurement Modelmentioning

confidence: 99%

Contributions to automated realtime underwater navigation

Stanway¹

2012

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This dissertation presents three separate-but related-contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field-some have been demonstrated in all three arenas.The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors.The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current-the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. 3Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework-without altering the filter structure or requiring any ad-hoc adjust...

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“…However, GNSS signals are inaccessible to AUVs. As such, acoustic navigation systems can be applied, the nodes of which must be installed and calibrated carefully [3,4]. Considering the resource demands of time and cost, an inertial navigation system (INS) is an alternative used to estimate the velocities and positions of AUVs with excellent short-term precision [5].…”

Section: Introductionmentioning

confidence: 99%

Particle filter underwater terrain-aided navigation based on gradient fitting

Zhou¹,

Wang²,

Gao³

et al. 2022

Meas. Sci. Technol.

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The Inertial Navigation System (INS) is widely used for Autonomous Underwater Vehicles (AUVs) navigation with excellent short-term precision. However, the positioning error of INS accumulates along with time. It is imperative to appeal to other approaches to mitigate drift errors, especially for long-term sailing tasks. To that end, underwater Terrain Based Navigation (TBN) is effective in bounding the drift errors. In particular, the particle filtering (PF) method is extensively employed in TBN to tackle the highly nonlinear measurement equation. In our previous work, the statistical properties of the Digital Terrain Model (DTM) gradient were exploited, and we proposed to use three probability density functions (PDFs) to characterize the normalized data, i.e., Gaussian, Gamma and Weibull distributions. In this paper, the likelihood was modified according to the gradient fitting results, i.e., an optimal distribution selection. Moreover, to prevent the measurement data with large gradients from generating particles with lower weights, a pre-screen procedure was proposed to stabilize PF sampling. As shown and demonstrated in simulations, our proposed improved PF method outperforms the other comparative ones in terms of Root Mean Square Error (RMSE) and stability, as well as accuracy, especially for flat terrain data. In terms of computation cost, employing smaller amount of measurement data, the proposed method is faster than the standard PF method.

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A parallel hypothesis method of autonomous underwater vehicle navigation

Cited by 8 publications

References 37 publications

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

Contributions to automated realtime underwater navigation

Particle filter underwater terrain-aided navigation based on gradient fitting

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