Sonar Based Delineation of Oil Plume Proxies Using an AUV

Hwang, Jimin; Bose, Neil; Robinson, Brian H.; Thanyamanta, Worakanok

doi:10.18178/ijmerr.11.4.207-214

Cited by 2 publications

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“…In preparation for field trials, we conducted simulation and tank tests to assess the acoustic features of different sized bubbles and the detection capacity of different sonars. This work extended our previous research, where we extensively examined three different sonars, each with a distinct frequency, against oil droplets and gas bubbles in a wave tank, along with micro air bubbles (100 to 500 microns) in a local lake [15]. Additionally, we conducted further tests using the Ping360 sonar against micro air bubbles (<100 microns) in an open ocean setting [16], and in a towing tank against micro air bubbles (100 to 250 microns) [17].…”

Section: Equipmentsupporting

confidence: 58%

“…The vehicle was equipped with an array of detection and collection instruments, including a scanning sonar (Ping360 of BlueRobotics), two fluorometer units-CDOM and PAH (UviLux of Chelsea Technologies), and a water sampling unit (multi water sampler of KC-Denmark). The Ping360 operates at a frequency of 750 Hz and has a maximum range of 50 m. In our previous published research we conducted tests comparing various sonar frequencies to assess their performance in detecting oil droplets [15]. Our findings indicated that higher frequency sonars exhibited superior detection capabilities for the smaller oil droplets.…”

Section: Equipmentmentioning

confidence: 81%

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Adaptive AUV Mission Control System Tested in the Waters of Baffin Bay

Hwang,

Bose,

Millar

et al. 2024

Drones

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The primary objectives of this paper are to test an adaptive sampling method for an autonomous underwater vehicle, specifically tailored to track a hydrocarbon plume in the water column. An overview of the simulation of the developed applications within the autonomous system is presented together with the subsequent validation achieved through field trials in an area of natural oil seeps near to Scott Inlet in Baffin Bay. This builds upon our prior published work in methodological development. The method employed involves an integrated backseat drive of the AUV, which processes in situ sensor data in real time, assesses mission status, and determines the next task. The core of the developed system comprises three modular components—Search, Survey, and Sample—each designed for independent and sequential execution. Results from tests in Baffin Bay demonstrate that the backseat drive operating system successfully accomplished mission goals, recovering water samples at depths of 20 m, 50 m, and 200 m before mission completion and vehicle retrieval. The principal conclusion drawn from these trials underscores the system’s resilience in enhanced decision autonomy and validates its applicability to marine pollutant assessment and mitigation.

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Section: Equipmentsupporting

confidence: 58%

Section: Equipmentmentioning

confidence: 81%

Adaptive AUV Mission Control System Tested in the Waters of Baffin Bay

Hwang,

Bose,

Millar

et al. 2024

Drones

Self Cite

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Bubble Plume Tracking Using a Backseat Driver on an Autonomous Underwater Vehicle

Hwang,

Bose,

Millar

et al. 2023

Drones

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Autonomous underwater vehicles (AUVs) have been applied in various scientific missions including oceanographic research, bathymetry studies, sea mine detection, and marine pollution tracking. We have designed and field-tested in the ocean a backseat driver autonomous system for a 5.5 m survey-class Explorer AUV to detect and track a mixed-phase oil plume. While the first driver is responsible for controlling and safely operating the vehicle; the second driver processes real-time data surrounding the vehicle based on in situ sensor measurements and adaptively modifies the mission details. This adaptive sensing and tracking method uses the Gaussian blur and occupancy grid method. Using a large bubble plume as a proxy, our approach enables real-time adaptive modifications to the AUV’s mission details, and field tests show successful plume detection and tracking. Our results provide for remote detection of underwater oil plumes and enhanced autonomy with these large AUVs.

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Sonar Based Delineation of Oil Plume Proxies Using an AUV

Cited by 2 publications

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Adaptive AUV Mission Control System Tested in the Waters of Baffin Bay

Adaptive AUV Mission Control System Tested in the Waters of Baffin Bay

Bubble Plume Tracking Using a Backseat Driver on an Autonomous Underwater Vehicle

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