无人机自动接力追踪鲨鱼，突破单机续航限制。
Continuous Marine Tracking via Autonomous UAV Handoff
- 多无人机协同追踪，通过高置信度特征匹配实现无缝交接。
- 实测跟踪成功率81.9%，目标覆盖率达82.9%，抗光照与遮挡干扰。
- 适合海洋生物长期监控，为自动化野外观测提供新方案。
本文提出一种基于自主无人机的连续实时海洋动物追踪系统，聚焦动态海况下鲨鱼的视觉追踪。系统集成机载计算机、稳定化RGB-D相机及定制训练的OSTrack追踪管道，在复杂光照、遮挡与海况条件下实现精准识别。核心创新为多无人机间的手动交接协议，通过高置信度特征匹配实现追踪责任无缝转移，突破单机电池续航限制。在包含5,200帧的鲨鱼数据集上评估，实时飞行控制下（100 Hz）跟踪成功率达81.9%，对遮挡、光照变化及背景杂波具有强鲁棒性。手控交接框架实现82.9%的目标覆盖率。结果验证了协同无人机操作在长时间海洋追踪中的可行性，为可扩展的自主监测奠定基础。
原文摘要 · Abstract (English)
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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