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基于单目视觉与测距信息的无人机集群定位方法

李坤 布树辉 李佳朋 王俱博玺 韩鹏程 李霄翰 李浩玮

航空学报2025,Vol.46Issue(11):300-320,21.
航空学报2025,Vol.46Issue(11):300-320,21.DOI:10.7527/S1000-6893.2024.31281

基于单目视觉与测距信息的无人机集群定位方法

UAV swarm positioning method based on monocular vision and ranging information

李坤 1布树辉 1李佳朋 1王俱博玺 1韩鹏程 1李霄翰 1李浩玮1

作者信息

  • 1. 西北工业大学 航空学院,西安 710072||飞行器基础布局全国重点实验室,西安 710072
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摘要

Abstract

Unmanned Aerial Vehicle(UAV)swarms play a pivotal role in the low-altitude economy.Accurate swarm positioning information underpins mission coordination,resource optimization,and efficient scheduling among drones,thereby facilitating the sustainable advancement of the low-altitude economy.In complex environments,however,Global Satellite Navigation System(GNSS)signals may be disrupted,rendering it difficult for UAV swarms to obtain accurate positioning data and compromising their ability to function collaboratively.To address this challenge in GNSS-denied environments,this paper presents a UAV swarm positioning method that integrates monocular vision and rang-ing information.Visual Odometry(VO)is employed to enable autonomous positioning for each UAV within the swarm.A communication framework is designed to transmit only essential data,including visual keyframes,pose frames,and map points,to the central server,thus reducing communication bandwidth.The concept of pose frame is introduced to address the limitation that keyframes cannot fuse with ranging information.The central server aligns maps from dif-ferent UAVs based on the common view relationships between keyframes or the constraints between pose frames and their corresponding ranging data.The server then fuses and optimizes these maps using both visual and ranging infor-mation,achieving accurate swarm positioning.After global optimization,the server sends the corrected keyframe and map point data back to the local map of UAV's VO to further enhance positioning accuracy.The proposed method is validated through simulations and experiments.Results demonstrate that the swarm positioning error is reduced to 0.49 m,outperforming current state-of-the-art visual positioning methods.Additionally,the scale error is reduced to 3.2%,effectively resolving the problem of scale ambiguity inherent in monocular visual positioning.This method pro-posed enables precise UAV swarm positioning based solely on inter-UAV ranging information,eliminating the need for shared visual features,and providing robust positioning data for UAV swarms operating in complex environments.

关键词

无人机集群/视觉定位/距离测量/集群定位/图优化

Key words

UAV swarm/visual positioning/range measurement/swarm positioning/graph optimization

分类

航空航天

引用本文复制引用

李坤,布树辉,李佳朋,王俱博玺,韩鹏程,李霄翰,李浩玮..基于单目视觉与测距信息的无人机集群定位方法[J].航空学报,2025,46(11):300-320,21.

基金项目

国家资助博士后研究人员计划(GZB20240986) Postdoctoral Fellowship Program of CPS(GZB20240986) (GZB20240986)

航空学报

OA北大核心

1000-6893

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