Real-Time Guidance of Underwater Gliders Assisted by Predictive Ocean Models

Chang, Dongsik; Zhang, Fumin; Edwards, Catherine

doi:10.1175/jtech-d-14-00098.1

Cited by 53 publications

(37 citation statements)

References 33 publications

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“…The criteria that tests whether the glider can move along desired direction is presented in Ref. [39]. LEC with ocean flow: Since ocean flow influences the speed of the glider, the motion time in the energy consumption model is changed by flow speed.…”

Section: Flow Estimate and Motion Correctionmentioning

confidence: 99%

Coordinate Control, Motion Optimization and Sea Experiment of a Fleet of Petrel-II Gliders

Xue

Wang

et al. 2018

Chin. J. Mech. Eng.

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The formation of hybrid underwater gliders has advantages in sustained ocean observation with high resolution and more adaptation for complicated ocean tasks. However, the current work mostly focused on the traditional gliders and AUVs. The research on control strategy and energy consumption minimization for the hybrid gliders is necessary both in methodology and experiment. A multi-layer coordinate control strategy is developed for the fleet of hybrid underwater gliders to control the gliders' motion and formation geometry with optimized energy consumption. The inner layer integrated in the onboard controller and the outer layer integrated in the ground control center or the deck controller are designed. A coordinate control model is proposed based on multibody theory through adoption of artificial potential fields. Considering the existence of ocean flow, a hybrid motion energy consumption model is constructed and an optimization method is designed to obtain the heading angle, net buoyancy, gliding angle and the rotate speed of screw propeller to minimize the motion energy with consideration of the ocean flow. The feasibility of the coordinate control system and motion optimization method has been verified both by simulation and sea trials. Simulation results show the regularity of energy consumption with the control variables. The fleet of three Petrel-II gliders developed by Tianjin University is deployed in the South China Sea. The trajectory error of each glider is less than 2.5 km, the formation shape error between each glider is less than 2 km, and the difference between actual energy consumption and the simulated energy consumption is less than 24% actual energy. The results of simulation and the sea trial prove the feasibility of the proposed coordinate control strategy and energy optimization method. In conclusion, a coordinate control system and a motion optimization method is studied, which can be used for reference in theoretical research and practical fleet operation for both the traditional gliders and hybrid gliders.

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Section: Flow Estimate and Motion Correctionmentioning

confidence: 99%

Coordinate Control, Motion Optimization and Sea Experiment of a Fleet of Petrel-II Gliders

Xue

Wang

et al. 2018

Chin. J. Mech. Eng.

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“…The dead-reckoned trajectoryr(t) can be predicted using equation (1). However, the actual trajectory r(t) is usually unknown due to the unknown flow velocity f (r, t).…”

Section: Background: Glider Operationmentioning

confidence: 99%

“…Since the differences between the GPS "fix" and the dead-reckoned surfacing positions serve as a direct in-situ measurements of the unknown depth-averaged flow velocity along glider trajectories, they can be used as a source for data assimilation as shown in previous glider deployments [8,1,2]. The resulting ocean models can then be used to navigate the gliders.…”

Section: Introductionmentioning

confidence: 99%

“…The resulting ocean models can then be used to navigate the gliders. Various algorithms have been proposed that integrate ocean model predictions into path planning and trajectory design for AUVs [6,14,23,15,18,1]. However, it is known that flow velocity data assimilation for ocean models is a challenging problem because of the relatively sparse and inaccurate in situ measurements of current velocity, and existing ocean models usually have low temporal and spatial resolution relative to the scales of glider motion [9,17,5].…”

Section: Introductionmentioning

confidence: 99%

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Glider CT

Chang

Zhang

2013

Proceedings of the Eighth ACM International Conference on Underwater Networks and Systems - WUWNet '13

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The motion of underwater gliders is strongly affected by ocean currents, which would benefit from a precise map of flow velocity with fine resolution. In this paper, we propose a novel method for reconstructing depth-averaged flow fields leveraging a motion prediction system. The method is based on the fact that the difference between the actual GPS location where a glider comes to the surface and the predicted surfacing position is determined by a line integral of depth-averaged ocean currents along the underwater trajectory of the glider. Even though the underwater trajectories of a glider can not be directly observed, the motion prediction system can be employed to estimate such trajectories. When multiple gliders are involved, we are able to formulate the problem of reconstructing a depth-averaged flow field as a nonlinear estimation problem that has strong connections with algorithms in computerized tomography (CT). However, extensions to CT algorithms are necessary due to the nonlinear nature and practical constraints of the flow reconstruction problem. As a first step towards solving this problem, this paper develops iterative algorithms with demonstrated success in simulations.

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“…Different from this work, Chang et al [35] proposed a real-time guidance system for underwater gliders using predictive ocean models in combination with glider-derived flow estimate to improve the gliders' navigation performance in complex flow regions with large spatial and temporal flow changes. Their navigation scheme focuses on gliders that perform dead reckoning using depth and attitude sensors instead of initial navigation systems and requires the vehicles to resurface at regular intervals.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Inertial Navigation Aided by Dynamics of Flow Field Features

Song

Mohseni

2018

IEEE J. Oceanic Eng.

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A current-aided inertial navigation framework is proposed for small autonomous underwater vehicles in longduration operations (> 1 hour), where neither frequent surfacing nor consistent bottom-tracking are available. We instantiate this concept through mid-depth, underwater navigation. This strategy mitigates dead-reckoning uncertainty of a traditional inertial navigation system by comparing the estimate of local, ambient flow velocity with preloaded ocean current maps. The proposed navigation system is implemented through a marginalized particle filter where the vehicle's states are sequentially tracked along with sensor bias and local turbulence that is not resolved by general flow prediction. The performance of the proposed approach is first analyzed through Monte Carlo simulations in two artificial background flow fields, resembling real-world ocean circulation patterns, superposed with smaller-scale, turbulent components with Kolmogorov energy spectrum. The current-aided navigation scheme significantly improves the dead-reckoning performance of the vehicle even when unresolved, small-scale flow perturbations are present. For a 6-hour navigation with an automotive-grade inertial navigation system, the currentaided navigation scheme results in positioning estimates with under 3% uncertainty per distance traveled (UDT) in a turbulent, double-gyre flow field, and under 7.3% UDT in a turbulent, meandering jet flow field. Further evaluation with field test data and actual ocean simulation analysis demonstrates consistent performance for a 6-hour mission, positioning result with under 25% UDT for a 24-hour navigation when provided direct heading measurements, and terminal positioning estimate with 16% UDT at the cost of increased uncertainty at an early stage of the navigation.

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Real-Time Guidance of Underwater Gliders Assisted by Predictive Ocean Models

Cited by 53 publications

References 33 publications

Coordinate Control, Motion Optimization and Sea Experiment of a Fleet of Petrel-II Gliders

Coordinate Control, Motion Optimization and Sea Experiment of a Fleet of Petrel-II Gliders

Glider CT

Long-Term Inertial Navigation Aided by Dynamics of Flow Field Features

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