Evaluation of AUV-based ADCP measurements

Fong, Derek A.; Jones, Nicole L.

doi:10.4319/lom.2006.4.58

Cited by 49 publications

(24 citation statements)

References 19 publications

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“…Our earlier work has shown that the REMUS ADCP can be effective in resolving steady BL structure with spatial averaging of 50-100m (Jaramillo & Pawlak, 2010a). Analysis of along-track velocities has shown evidence of weak velocity bias in the direction of platform motion in agreement with other observations from vessel and AUV-mounted ADCPs (Fong & Monismith, 2004;Fong & Jones, 2006). In Jaramillo & Pawlak (2010a), we further characterize the variability in this bias with sampling.…”

Section: Approachsupporting

confidence: 86%

Hydrodynamics and Roughness of Irregular Boundaries

Pawlak¹

2010

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LONG-TERM GOALSThe research goals of the work target accurate parameterization and modeling of nearshore waves, currents and turbulence in complex reef environments. A central theme of this work is the response of steady and oscillating flow to highly irregular, broad-banded roughness. Previous ONR supported study by the PI's group have quantified reef roughness, examined the hydrodynamic response to a variable roughness at small scales and explored the relationship between hydrodynamic and physical roughness. OBJECTIVESSpecifically, the work aims to examine methods for quantifying physical roughness scales in reef environments using an autonomous underwater vehicle (AUV) and to determine the hydrodynamically relevant roughness scales for wave and current flow.The work underway is also enabling development of a series of practical applications including examination of the relationship between measured roughness and sidescan imagery, exploration of AUV-based ADCP observations for resolution of steady flow boundary layer dynamics, and implementation of new tools for measurement of turbulent stresses in wavy environments. In addition high-resolution reef morphology data will enable further study on the correlation between roughness and other measurable reef characteristics including coral color, health and species. APPROACHTo achieve the objectives detailed above, we are conducting a series of focused field experiments targeting resolution of flow hydrodynamics over a range of reef environments in varying wave and current conditions, with concurrent high resolution roughness mapping. The first series of observations are being carried out at the Kilo Nalu Observatory on the south shore of Oahu (Pawlak et al, 2009; www.soest.hawaii.edu/OE/KiloNalu/). A second set of observations is also being carried out in Guam in October, 2010 leveraging funding from the Army Corps of Engineers in collaboration with Mark Merrifield (UH Oceanography). A third set of field observations is targeted for the north shore of Oahu for winter, 2011.

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Section: Approachsupporting

confidence: 86%

Hydrodynamics and Roughness of Irregular Boundaries

Pawlak¹

2010

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“…Results of missions performed in 2011 by OSU off the Oregon Shelf and in the Sargasso Sea are available in [8]. It is important to note that errors or missing data may occur in current measurement from on-board ADCP/DVL [9]. The ADCP manufacturer claims to have an accuracy of 1 % of the measured current magnitude ± 5mm/s.…”

Section: Introductionmentioning

confidence: 98%

Efficient Path Re-planning for AUVs Operating in Spatiotemporal Currents

Zeng

Sammut

Lammas

et al. 2014

J Intell Robot Syst

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This paper presents an on-line dynamic path re-planning system for an autonomous underwater vehicle (AUV) to enable it to operate efficiently in a spatiotemporal, cluttered, and uncertain environment. The proposed strategy combines path re-planning with an evolutionary algorithm to adapt and regenerate the trajectory during the course of the mission using continuously updated current profiles from on-board sensors, such as a Horizontal Acoustic Doppler Velocity Logger. A quantumbehaved particle swarm optimization (QPSO) algorithm is used with a cost function which is based on the total time required to travel along the path segments accounting for the effect of space-time variable currents. The proposed path planner is designed to generate an optimal trajectory for an AUV navigating through a spatiotemporal ocean environment in the presence of irregularly shaped terrains as well as obstacles whose position coordinates are uncertain. Simulation results show that using the same on-board computation resources, the proposed path re-planning methodology with reuse of information gained from the previous planning history is able to obtain a more optimized trajectory than one relying on reactive path planning. Subsets of representative Monte Carlo simulations were run to analyse the performance of these dynamic planning systems. The results demonstrate the inherent robustness and superiority of the proposed planner based on path re-planning scheme when compared with the reactive path planning scheme.

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“…Acoustic Doppler Current Profilers (ADCPs) were originally implemented by scientists on aquatic AVs to provide dead-reckoning navigation based on a Doppler Velocity Log (DVL) [7]. However, ADCPs have recently been used on AVs to measure features including coastal ocean flows [1,5,7,13,18], directional surface waves [12], and depthaveraged currents [6]. There is an increasing need for collecting environmental data with AVs in faster and more dynamic flows found in riverine and estuarine environments.…”

Section: Introductionmentioning

confidence: 99%

“…In order to ensure a true estimate of the mean velocity is obtained when evaluating an appropriate averaging window, and to eliminate errors due to spatial variability from moving-vessel measurements, only measurements obtained by the vessels at fixed locations are considered in this work. Acoustic Doppler Current Profilers (ADCPs) were originally implemented by scientists on aquatic AVs to provide dead-reckoning navigation based on a Doppler Velocity Log (DVL) [7]. However, ADCPs have recently been used on AVs to measure features including coastal ocean flows [1,5,7,13,18], directional surface waves [12], and depthaveraged currents [6].…”

Section: Introductionmentioning

confidence: 99%

The use of autonomous vehicles for spatially measuring mean velocity profiles in rivers and estuaries

Brown

Tuggle

MacMahan

et al. 2011

Intel Serv Robotics

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Autonomous vehicles (AVs) are commonly used in oceanic and more recently estuarine and riverine environments because they are small, versatile, efficient, moving platforms equipped with a suite of instruments for measuring environmental conditions. However, moving vessel observations, particularly those associated with Acoustic Doppler Current Profiler (ADCP) measurements, can be problematic owing to instrument noise, flow fluctuations, and spatial variability. A range of ADCPs manufactured by different companies were integrated on to an Unmanned Surface Vehicle (USV), an Unmanned Underwater Vehicle (UUV), and some additional stationary platforms and were deployed in a number of natural riverine and estuarine environments to evaluate the quality of the velocity profile over the depth, minimum averaging time interval requirements, and AV mission planning considerations. Measurements were obtained at fixed locations to eliminate any spatial variations in the mean flow characteristics. The USV has the unique capability to station-keep to within 1 m owing to its dual-propeller design, providing the best setup for spatially mapping velocity profiles. Single-propeller UUVs can perform a quasi-stationkeeping (<10 m) operation, but are designed for traveling underwater at speeds >1 m/s. An appropriate averaging window, T * , was determined using the Kalman Algorithm with a Kalman gain equal to 1%. T * was found to be independent of depth, flow velocity, and environment. There was no

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Evaluation of AUV-based ADCP measurements

Cited by 49 publications

References 19 publications

Hydrodynamics and Roughness of Irregular Boundaries

Hydrodynamics and Roughness of Irregular Boundaries

Efficient Path Re-planning for AUVs Operating in Spatiotemporal Currents

The use of autonomous vehicles for spatially measuring mean velocity profiles in rivers and estuaries

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