Continuous Marine Tracking via Autonomous UAV Handoff
Heegyeong Kim (1), Alice James (1), Avishkar Seth (1), Endrowednes Kuantama (1), Jane Williamson (2), Yimeng Feng (1), Richard Han (1) ((1) School of Computing, Macquarie University, (2) School of Natural Sciences, Macquarie University)

TL;DR
This paper presents an autonomous UAV system for continuous marine animal tracking, featuring a novel inter-UAV handoff protocol that enhances coverage and robustness in challenging marine environments.
Contribution
It introduces a seamless UAV handoff framework and demonstrates its effectiveness for extended, real-time marine animal tracking in dynamic conditions.
Findings
Achieved 81.9% tracking success rate on a shark dataset.
Handoff protocol reached 82.9% target coverage.
System proved robust to occlusion and lighting changes.
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…
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Taxonomy
TopicsMaritime Navigation and Safety · Underwater Vehicles and Communication Systems
