Continuous Marine Monitoring via Autonomous UAV Handoff

This paper introduces an autonomous UAV vision system for continuous, real-time tracking of marine animals, specifically sharks, in dynamic marine environments. The system integrates an onboard computer with a stabilised RGB-D camera and a custom-trained OSTrack pipeline, enabling visual identification under challenging lighting, occlusion, and sea-state conditions. A key innovation is the inter-UAV handoff protocol, which enables seamless transfer of tracking responsibilities between drones, extending operational coverage beyond single-drone battery limitations. Performance is evaluated on a curated shark dataset of 5,200 frames, achieving a tracking success rate of 81.9% during real-time flight control at 100 Hz, and robustness to occlusion, illumination variation, and background clutter. We present a seamless UAV handoff framework, where target transfer is attempted via high-confidence feature matching, achieving 82.9% target coverage. These results confirm the viability of coordinated UAV operations for extended marine tracking and lay the groundwork for scalable, autonomous monitoring.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3711875.3737661
Citations
2
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
2.29
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Continuous Marine Monitoring via Autonomous UAV Handoff

Jane E. Williamson, Yimeng Feng, Endrowednes Kuantama, Avishkar Seth et al.
2 citations
Underwater Vehicles and Communication Systems
2.29
article

Continuous Marine Monitoring via Autonomous UAV Handoff

Jane E. Williamson, Yimeng Feng, Endrowednes Kuantama, Avishkar Seth, Heegyeong Kim, Richard Han, Alice James
article en
2 citations

Abstract

This paper introduces an autonomous UAV vision system for continuous, real-time tracking of marine animals, specifically sharks, in dynamic marine environments. The system integrates an onboard computer with a stabilised RGB-D camera and a custom-trained OSTrack pipeline, enabling visual identification under challenging lighting, occlusion, and sea-state conditions. A key innovation is the inter-UAV handoff protocol, which enables seamless transfer of tracking responsibilities between drones, extending operational coverage beyond single-drone battery limitations. Performance is evaluated on a curated shark dataset of 5,200 frames, achieving a tracking success rate of 81.9% during real-time flight control at 100 Hz, and robustness to occlusion, illumination variation, and background clutter. We present a seamless UAV handoff framework, where target transfer is attempted via high-confidence feature matching, achieving 82.9% target coverage. These results confirm the viability of coordinated UAV operations for extended marine tracking and lay the groundwork for scalable, autonomous monitoring.

Macquarie University (AU)
Openalex Percentile: Top 11%
Underwater Vehicles and Communication Systems
2.29
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