PATH: Continuous Target Sensing among Autonomous Cooperative Drones

2026-09-11

AI Summary

为解决无人机因续航限制导致的连续目标跟踪问题，本文提出PATH框架，利用几何辅助方法实现两架移动无人机间的目标交接。

Abstract

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.

Problem

• Continuous Target Sensing
• Cooperative Drones
• Tracking Handoff

Innovation

• Perspective Alignment
• Tracking Handoff
• RGB-D sensing
• geometry-assisted
• Mutual Agreement Handshake