CVROJul 17, 2025

Continuous Marine Tracking via Autonomous UAV Handoff

arXiv:2507.12763v11 citationsh-index: 13
Originality Incremental advance
AI Analysis

This enables extended marine monitoring beyond single-drone battery limits, though it is incremental as it adapts existing tracking methods to a new application.

The paper tackles continuous tracking of marine animals (sharks) in dynamic environments using an autonomous UAV vision system with inter-UAV handoff, achieving 81.9% tracking success rate on 5,200 frames and 82.9% target coverage during handoffs.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes