PATH：自主协作无人机中的连续目标感知

中文摘要 AI 辅助

无人驾驶飞行器（UAV）的连续目标感知受限于有限的飞行续航能力，这促使了跟踪责任在协作无人机之间的转移。这种交接要求接收方识别发送方当前跟踪的同一物理目标，尽管存在视点、尺度和目标外观的差异。现有的基于全局目标定位或基于外观的跨视角关联方法受限于定位不确定性或模糊的视觉特征。本文提出了视角对齐与跟踪交接（PATH），一种平台无关、几何辅助的感知与验证框架，用于两架移动无人机之间的目标交接。发送方使用RGB-D感知将跟踪目标重建为度量三维点，而接收方通过基准标记观测估计其相对位姿，并将传输的目标点投影到自身图像中作为目标获取的空间先验。随后，接收方生成的候选被返回给发送方，并通过跨视角相互协议握手进行验证，之后才转移跟踪责任。真实世界无人机实验显示，平均相对位置误差和目标位置误差分别为0.047米和0.030米。在视觉模糊条件下，PATH实现了96.0%的帧级接收方目标获取准确率，误报率和漏报率分别为2.0%和2.0%。传感器误差敏感性分析表明，相对位姿不确定性是接收方视角投影误差的主要贡献因素。该实现以视频速率运行，紧凑的无人机间通信在60赫兹下低于16千字节/秒，展示了在资源受限的无人机平台上轻量级几何辅助目标交接的可行性。

英文摘要

Continuous target sensing by uncrewed aerial vehicles (UAVs) is constrained by limited flight endurance, motivating the transfer of tracking responsibility between cooperating UAVs. Such a handoff requires the receiver to identify the same physical target currently tracked by the sender despite differences in viewpoint, scale, and target appearance. Existing approaches based on global target localization or appearance-based cross-view association are limited by positioning uncertainty or ambiguous visual features. This paper presents Perspective Alignment \& Tracking Handoff (\textbf{PATH}), a platform-agnostic, geometry-assisted sensing and verification framework for target handoff between two moving UAVs. The sender reconstructs the tracked target as a metric 3D point using RGB-D sensing, while the receiver estimates its relative pose from a fiducial observation and projects the transmitted target point into its own image as a spatial prior for target acquisition. The receiver-generated candidate is then returned to the sender and verified through a cross-view Mutual Agreement Handshake before tracking responsibility is transferred. Real-world UAV experiments show mean relative-position and target-position errors of 0.047~m and 0.030~m, respectively. Under visually ambiguous conditions, PATH achieves 96.0\% frame-level receiver-side target acquisition accuracy, with 2.0\% false-positive and 2.0\% false-negative rates. A sensor-error sensitivity analysis shows that relative-pose uncertainty is the dominant contributor to receiver-view projection error. The implementation operates at video rate with compact inter-UAV communication below 16~kB/s at 60~Hz, demonstrating the feasibility of lightweight geometry-assisted target handoff on resource-constrained UAV platforms.

发表机构

• Macquarie University（麦考瑞大学）

机构由 AI 辅助整理，请以论文原文为准。