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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yogesh Girdhar Nathan McGuire Levi Cai Stewart Jamieson Seth McCammon Brian Claus John E. San Soucie Jessica E. Todd T. Aran Mooney Woods Hole Oceanographic Institution (WHOI) MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering

The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation and complexity of interactions between different reef organisms and their habitat. The CUREE platform presented in this paper provides a unique set of capabilities in the form of robot behaviors and perception algorithms to enable scientists to explore different aspects of an ecosystem. Examples of these capabilities include low-altitude visual surveys, soundscape surveys, habitat characterization, and animal following. We demonstrate these capabilities by describing two field deployments on coral reefs in the US Virgin Islands. In the first deployment, we show that CUREE can identify the preferred habitat type of snapping shrimp in a reef through a combination of a visual survey, habitat characterization, and a soundscape survey. In the second deployment, we demonstrate CUREE's ability to follow arbitrary animals by separately following a barracuda and stingray for several minutes each in midwater and benthic environments, respectively.

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The abundance and localization of environmental microplastics in gastrointestinal tract and muscle of Atlantic killifish (Fundulus heteroclitus): a pilot study

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Microplastics and Nanoplastics 2024年第1期4卷 23页

作者： Pitt, Jordan A. Gallager, Scott M. Youngs, Sarah Michel, Anna P. M. Hahn, Mark E. Aluru, Neelakanteswar Biology Department Woods Hole Oceanographic Institution Woods Hole 02543 MA United States Massachusetts Institute of Technology (MIT) – Woods Hole Oceanographic Institution (WHOI) Joint Graduate Program in Oceanography and Oceanographic Engineering Woods Hole 02543 MA United States CoastalOceanVision Inc 10 Edgerton Drive North Falmouth 02556 MA United States Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole 02543 MA United States

Microplastics (MPs) have been found in a diverse range of organisms across trophic levels. While a majority of the information on organismal exposure to plastics in the environment comes from gastrointestinal (GI) data, the prevalence of MP particles in other tissues is not well understood. Additionally, many studies have not been able to detect the smallest, most prevalent, MPs (1 µm – 5 mm) that are the most likely to distribute to tissues in the body. To address these knowledge gaps, MPs in the GI tract and muscle of Atlantic killifish (Fundulus heteroclitus) collected from two sites (Falmouth and Bourne) on Buzzards Bay, Cape Cod, MA were quantified down to 2 µm in size. Eight fish from Falmouth and 10 fish Bourne site were analyzed. Fourier-transform infrared spectroscopy and Raman spectroscopy were used to identify all particles. The mean concentrations of MPs in the GI tract and muscle from fish collected from Falmouth was 85.5 ± 70.2 and 11 ± 12.5 particles per gram wet weight, respectively. Fish collected from Bourne site had mean particle concentrations of 12.2 ± 18.1 and 1.69 ± 5.36 particles per gram wet weight. Of the 2,008 particles analyzed in various fish tissue samples, only 3.4% (69 particles) were identified as plastic;polymers included nylon, polyethylene, polypropylene, and polyurethane. MPs detected in the GI tract samples also tended to be more diverse in both size and polymer type than those found in the muscle. We found that MPs < 50 µm, which are often not analyzed in the literature, were the most common in both the GI tract and muscle samples. There was not a significant correlation between the MP content in the muscle compared to the GI tract, indicating that GI tract MP abundance cannot be used to predict non-GI tract tissue MP content;however, MP abundance in muscle correlated with fish total length, suggesting potential bioaccumulation of these small MPs. © The Author(s) 2024.

关键词： Bioaccumulation Fish Fourier-transform infrared spectroscopy Microplastics Raman spectroscopy Translocation

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Discovering Biological Hotspots with a Passively Listening AUV

Discovering Biological Hotspots with a Passively Listening A...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Seth McCammon Stewart Jamieson T. Aran Mooney Yogesh Girdhar Woods Hole Oceanographic Institution (WHOI) Woods Hole MA Department of Aeronautics and Astronautics MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering Massachusetts Institute of Technology (MIT)

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We present a novel system which blends multiple distinct sensing modalities in audio-visual surveys to assist marine biologists in collecting datasets for understanding the ecological relationship of fish and other organisms with their habitats on and around coral reefs. Our system, designed for the CUREE AUV, uses four hydrophones to determine the bearing to biological sound sources through beamforming. These observations are merged in a Bayesian Occupancy Grid to produce a 2D map of the acoustic activity of a coral reef. Simultaneously, the AUV uses unsupervised topic modeling to identify different benthic habitats. Combining these maps allows us to determine the level of acoustic activity within each habitat. We demonstrated the system in field trials on reefs in the U.S. Virgin Islands, where it was able to autonomously discover the favored habitats of snapping shrimp (genus Alpheus).

关键词： Surveys Temperature measurement Visualization Array signal processing Habitats Marine vegetation Fish

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Correction: Oceanic bottom mixed layer in the Clarion-Clipperton Zone: potential influence on deep-seabed mining plume dispersal

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Environmental Fluid Mechanics 2024年第6期24卷 1443-1444页

作者： Chen, Si-Yuan Sean Ouillon, Raphael Muñoz-Royo, Carlos Peacock, Thomas Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge USA Department of Physical Oceanography Woods Hole Oceanographic Institution Woods Hole USA MIT-WHOI Joint Program in Oceanography Massachusetts Institute of Technology Cambridge USA

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DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods

DeepSeeColor: Realtime Adaptive Color Correction for Autonom...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Stewart Jamieson Jonathan P. How Yogesh Girdhar MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering Department of Aeronautics and Astronautics Massachusetts Institute of Technology (MIT) Applied Ocean Physics and Engineering Department Woods Hole Oceanographic Institution (WHOI)

Successful applications of complex vision-based behaviours underwater have lagged behind progress in terrestrial and aerial domains. This is largely due to the degraded image quality resulting from the physical phenomena involved in underwater image formation. Spectrally-selective light attenuation drains some colors from underwater images while backscattering adds others, making it challenging to perform vision-based tasks underwater. State-of-the-art methods for underwater color correction optimize the parameters of image formation models to restore the full spectrum of color to underwater imagery. However, these methods have high computational complexity that is unfavourable for realtime use by autonomous underwater vehicles (AUVs), as a result of having been primarily designed for offline color correction. Here, we present DeepSeeColor, a novel algorithm that combines a state-of-the-art underwater image formation model with the computational efficiency of deep learning frameworks. In our experiments, we show that DeepSeeColor offers comparable performance to the popular “Sea-Thru” algorithm [1] while being able to rapidly process images at up to 60Hz, thus making it suitable for use onboard AUVs as a preprocessing step to enable more robust vision-based behaviours.

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A modern approach to the Kelvin-Helmholtz instability on circular vortex sheets

arXiv

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arXiv 2024年

作者： Wilcox, Galen Murray, Ryan MIT WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering Woods Hole MA United States MIT WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering CambridgeMA United States North Carolina State University RaleighNC United States

We represent the outermost shear interface of a eddy by a circular vortex sheet in two dimensions, and provide a new proof of linear instability via the Birkhoff-Rott equation. Like planar vortex sheets, circular sheets are found to be susceptible to a violent shortwave instability known as the Kelvin-Helmholtz instability, with some modifications due to vortex sheet geometry. This result is in agreement with the classical derivation of [35, 49], but our modern approach provides greater clarity. We go on to show that the linear evolution problem can develop a singularity from analytic initial data in a time proportional to the square of the vortex sheet radius. Numerical evidence is presented that suggests this linear instability captures the wave-breaking mechanism observed in nonlinear point vortex simulations. Based on these results, we hypothesize that the Kelvin-Helmholtz instability can contribute to the development of secondary instability for eddies in two-dimensional turbulent flow. Copyright © 2024, The Authors. All rights reserved.

关键词： Turbulent flow

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CUREE: A Curious Underwater Robot for Ecosystem Exploration

arXiv

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arXiv 2023年

作者： Girdhar, Yogesh McGuire, Nathan Cai, Levi Jamieson, Stewart McCammon, Seth Claus, Brian Soucie, John San E. Todd, Jessica E. Mooney, T. Aran United States MIT-WHOI Joint Program in Oceanography Applied Ocean Science and Engineering United States

The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation and complexity of interactions between different reef organisms and their habitat. The CUREE platform presented in this paper provides a unique set of capabilities in the form of robot behaviors and perception algorithms to enable scientists to explore different aspects of an ecosystem. Examples of these capabilities include low-altitude visual surveys, soundscape surveys, habitat characterization, and animal following. We demonstrate these capabilities by describing two field deployments on coral reefs in the US Virgin Islands. In the first deployment, we show that CUREE can identify the preferred habitat type of snapping shrimp in a reef through a combination of a visual survey, habitat characterization, and a soundscape survey. In the second deployment, we demonstrate CUREE’s ability to follow arbitrary animals by separately following a barracuda and stingray for several minutes each in midwater and benthic environments, respectively. © 2023, CC BY-NC-ND.

关键词： Ecosystems

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DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods

arXiv

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arXiv 2023年

作者： Jamieson, Stewart How, Jonathan P. Girdhar, Yogesh The MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering United States Applied Ocean Physics and Engineering Department

Successful applications of complex vision-based behaviours underwater have lagged behind progress in terrestrial and aerial domains. This is largely due to the degraded image quality resulting from the physical phenomena involved in underwater image formation. Spectrally-selective light attenuation drains some colors from underwater images while backscattering adds others, making it challenging to perform vision-based tasks underwater. State-of-the-art methods for underwater color correction optimize the parameters of image formation models to restore the full spectrum of color to underwater imagery. However, these methods have high computational complexity that is unfavourable for realtime use by autonomous underwater vehicles (AUVs), as a result of having been primarily designed for offline color correction. Here, we present DeepSeeColor, a novel algorithm that combines a state-of-the-art underwater image formation model with the computational efficiency of deep learning frameworks. In our experiments, we show that DeepSeeColor offers comparable performance to the popular "Sea-Thru" algorithm [1] while being able to rapidly process images at up to 60Hz, thus making it suitable for use onboard AUVs as a preprocessing step to enable more robust vision-based behaviours. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous underwater vehicles

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Adaptive multi-altitude search and sampling of sparsely distributed natural phenomena

Adaptive multi-altitude search and sampling of sparsely dist...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Jessica E. Todd Seth McCammon Yogesh Girdhar Nicholas Roy Dana Yoerger Department of Aeronautics and Astronautics MIT-WHOI Joint Program in Applied Ocean Science and Engineering at the Woods Hole Oceanographic Institution (WHOI) Massachusetts Institute of Technology (MIT) Applied Ocean Physics and Engineering Department Woods Hole Oceanographic Institution Woods Hole MA USA Department of Aeronautics and Astronautics Massachusetts Institute of Technology

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we propose a novel method for autonomously seeking out sparsely distributed targets in an unknown underwater environment. Our Sparse Adaptive Search and Sample (SASS) algorithm mixes low-altitude observations of discrete targets with high-altitude observations of the surrounding substrates. By using prior information about the distribution of targets across substrate types in combination with belief modelling over these substrates in the environment, high-altitude observations provide information that allows SASS to quickly guide the robot to areas with high target densities. A maximally informative path is autonomously constructed online using Monte Carlo Tree Search with a novel acquisition function to guide the search to maximise observations of unique targets. We demonstrate our approach in a set of simulated trials using a novel generative species model. SASS consistently outperforms the canonical boustrophedon planner by up to 36% in seeking out unique targets in the first 75-90% of time it takes for a boustrophedon survey. Additionally, we verify the performance of SASS on two real world coral reef datasets.

关键词： Surveys Adaptation models Monte Carlo methods Adaptive systems Marine vegetation Substrates Intelligent robots

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Corrigendum to “Non-linear singularity formation for circular vortex sheets”

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Quarterly of Applied Mathematics 2024年第2期82卷 449-450页

作者： Murray, Ryan Wilcox, Galen Department of Mathematics North Carolina State University Raleigh NC 27607 MIT-WHOI Joint Program in Oceanography/Applied Ocean Science & Engineering Cambridge MA 02139 and Woods Hole MA 02543

Abstract: This paper serves as a short corrigendum, describing an error in the derivation of the linearized equation. The main theorems remain correct, but they are based upon an incorrect linearization of the Birkhoff-Rott equation and hence are not directly applicable to the original physical problem.

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