针对目标间歇性失联，设计可自动切换跟踪与恢复模式的视觉追踪系统。
Visual Tracking with Intermittent Visibility: Switched Control Design and Implementation
- 通过切换跟踪与恢复模式，在保持距离和视野间取得平衡。
- 相比基线算法，平均追踪误差降低45%，可视时间显著延长。
- 适用于无人机等需应对视线中断的自主任务，参数选择有理论依据。
本文研究了追击者在目标间歇性失联场景下的视觉追踪问题。提出一种切换视觉追踪器（SVT），在维持与目标接近的同时，确保可见性。SVT在视觉跟踪模式与恢复模式间切换：前者用于持续跟随目标，后者在目标失联时重新建立视觉联系。通过扩展切换系统理论中的平均驻留时间定理，建立了SVT的稳定性分析，该分析具有独立研究价值。在Agilicious无人机上的实现表明，该方法能有效应对多种目标轨迹，平均追踪误差最多降低45%，且显著提升可视持续时间。结果验证了其在真实自主任务中具备更强鲁棒性与适应性。此外，稳定性分析为追踪速度、恢复距离等参数的选取提供了关键指导，有助于优化性能。
原文摘要 · Abstract (English)
This paper addresses the problem of visual target tracking in scenarios where a pursuer may experience intermittent loss of visibility of the target. The design of a Switched Visual Tracker (SVT) is presented which aims to meet the competing requirements of maintaining both proximity and visibility. SVT alternates between a visual tracking mode for following the target, and a recovery mode for regaining visual contact when the target falls out of sight. We establish the stability of SVT by extending the average dwell time theorem from switched systems theory, which may be of independent interest. Our implementation of SVT on an Agilicious drone [1] illustrates its effectiveness on tracking various target trajectories: it reduces the average tracking error by up to 45% and significantly improves visibility duration compared to a baseline algorithm. The results show that our approach effectively handles intermittent vision loss, offering enhanced robustness and adaptability for real-world autonomous missions. Additionally, we demonstrate how the stability analysis provides valuable guidance for selecting parameters, such as tracking speed and recovery distance, to optimize the SVT's performance.
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