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Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle

Seth McCammon, Levi Cai, Daniel Yang, Cast John, John Walsh, T. Aran Mooney, Yogesh Girdhar
May 10, 2026
Published Date

Research Abstract & Technology Focus

Dataset associated with McCammon et al. "Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle", Science Robotics. Associated data processing code is available at https://gitlab.com/whoi-smart-lab/papers/science_robotics_2025 Organization data.zip - ZIP archive containing all data required to reproduce Figures 1-7 JS_cross_survey audio_samples - folder containing .wav files used to detect fish calls js_orthomosaic_cross.png - raw PNG orthomosaic reconstruction from Joel's Shoal Cross Survey summary.csv - CSV File containing metadata for audio samples, including timestamp and position JS_grid_survey acoustic_map.csv - 2m resolution acoustic heatmap used to compute multimodal regressions fish_census.csv - CSV file containing raw data from fish census including position, time, and fish counts with various YOLO thresholds audio_samples - folder containing .wav files used to detect fish calls js_orthomosaic_grid.png - raw PNG orthomosaic reconstruction from Joel's Shoal Grid Survey js_rigosity.csv - 2m resolution rugosity map used to compute multimodal regressions js_rugosity_mesh.fbx - RAW mesh used to compute rugosity summary.csv - CSV File containing metadata for audio samples, including timestamp and position JS_homing js_homing1.mp4 - Downward-facing video from Joel's Shoal homing experiment 1 js_homing1_odom.csv - CSV file containing vehicle odometry from homing experiment 1 js_homing2.mp4 - Downward-facing video from Joel's Shoal homing experiment 2 js_homing2_odom.csv - CSV file containing vehicle odometry from homing experiment 2 JS_tracking 2022-11-03-barry-joelshoal-timesynced-with-autonomous-labels.mp4 - Timestamped video of full barracuda track with annotation to show manual/autonomous modes js_orthomosaic_tracking.png - raw PNG orthomosaic reconstruction from Joel's Shoal barracuda tracking experiment tracking_odom.csv - CSV file containing vehicle odometry from barracuda tracking experiment Lameshur_homing lameshur_homing1_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 1 lameshur_homing2_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 2 lameshur_homing3_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 3 lameshur_homing4_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 4 lameshur_homing5_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 5 lameshur_homing6_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 6 lameshur_homing7_odom.csv - CSV file containing vehicle odometry from lameshur homing experiment 7 scripts.zip - ZIP archive containing all code required to reproduce Figures 1-7. This is an archival snapshot of the code available on gitlab as of the publication date. Gitlab should be checked for the most up-to-date version as dependencies may receive updates/changes to APIs. reference README.md for installation/usage instructions Videos S01-S02 - Supplementary Videos. Video S01 - Video showing fish census with overlaid YOLO bounding boxes Video S02 - Video showing barracuda track with overlaid KeepTrackFast bounding box, timestamp, and vehicle mode Data Videos data01 - data11 - Other videos data01 - Downward-facing video from Joel's Shoal homing experiment 1 data02 - Downward-facing video from Joel's Shoal homing experiment 2 data03 - Manually-annotated diver video P7260010 used in Table S2 data04 - Manually-annotated diver video P7260012 used in Table S2 data05 - Manually-annotated diver video P5090348 used in Table S2 data06 - Manually-annotated diver video P5090349 used in Table S2 data07 - Manually-annotated diver video P5090350 used in Table S2 data08 - Manually-annotated diver video PA230380 used in Table S2 data09 - Manually-annotated diver video PA230381 used in Table S2 data10 - Manually-annotated diver video P1010039 used in Table S2 data11 - Manually-annotated diver video P1010041 used in Table S2 data12 - Manually-annotated diver video P1010042 used in Table S2
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Frequently Asked Questions (FAQ)

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What is the core focus of the research titled 'Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle'?

This literature focuses on: Dataset associated with McCammon et al. "Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle", Science Robotics. Associated data processing code is available at https://gitlab.com/whoi-smart-lab/papers/science_...

Are there open-source GitHub repositories related to Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle?

Yes, open-source projects like perplexityai/bumblebee (Read-only developer endpoint scanner for on-disk package, extension, and developer-tool metadata, built to check exposure to known software supply-...) are actively building upon these concepts.

Which startups are commercializing the technology behind Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle?

Products like Pegasus 1.5 by TwelveLabs are bringing this to market. Their focus is: AI model for transforming video into Time-Based Metadata.

What other academic literature is closely related to 'Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle'?

Yes, highly correlated activity was mapped. An entry titled 'Adaptive energy-efficient and secure clustering-based routing architecture for underwater wireless sensor networks in marine environmental and ecosystem monitoring' discusses this: Introduction Reliable long-term monitoring of coral reefs and other marine ecosystems is limited by the harsh underwater environment, restricted ba...

Are there commercial applications of 'Seeking and mapping coral reef biological hotspots with an autonomous underwater vehicle' in market news publications?

Yes, highly correlated activity was mapped. An entry titled 'How AI could unlock deep-sea secrets of marine life' discusses this: Robotic and autonomous underwater vehicles have collected vast quantities of footage from the deep sea, but most of it hasn’t been analysed.

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