Vision-Based Leader-Follower Formation Control for Cooperative UAVs in GPS-Degraded Environments

2026-09-01

AI Summary

本文提出一种基于视觉的无人机编队控制框架，使用RGB-D相机和YOLO检测器在GPS信号不佳环境中实时定位领航无人机，以维持跟随无人机的编队。

Abstract

Cooperation in multi-UAV systems requires reliable relative perception so that follower vehicles can maintain formation and continue their mission safely even when absolute positioning sensors degrade or fail. This paper presents a vision-based cooperative formation framework running on a follower UAV that uses a front-facing RGB-D camera to detect, track, and localize a leader UAV in real-time. A lightweight YOLO-based detector is trained on a dedicated drone dataset and deployed onboard to predict leader bounding boxes, which are then fused with depth information via a pinhole camera model to estimate the leader's relative pose. These estimates provide a leader-follower position controller and can also be used as a backup when GPS or external localization is unavailable. This framework is implemented as a set of ROS nodes and evaluated in a physics-based multi-UAV simulation built on XTDrone, with sensor noise and communication dropouts. We evaluate detection accuracy, runtime, and formation-keeping error under nominal conditions and under simulated failures of the positioning sensors. The results show that the proposed framework maintains stable leader-follower formations with reasonable computational cost and provides a practical basis for extending vision-based cooperative formation control to real-world multi-UAV systems.

Problem

• multi-UAV systems
• relative perception
• GPS-degraded environments
• formation control

Innovation

• vision-based formation control
• RGB-D camera
• YOLO-based detector
• pinhole camera model
• leader-follower