The Multi-UAV Collaborative Localization Based on Visual and Inertial Sensors

Guoda Cheng, Guoliang Yang, Deteng Zhang, Jinwen Hu, Jiancheng Zhang, Zhao Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Precise and robust navigation is a fundamental requirement for unmanned aerial vehicle (UAV) to perform various missions. In this paper, we propose a multi-UAV collaborative localization algorithm based on vector field consensus (VFC). VFC is employed to eliminate the incorrectly matched feature points, which significantly affect the localization accuracy. Moreover, we develop a real multi-UAV system with a centralized terminal to optimize the estimated state of UAVs, using transmission control protocol (TCP) as the communication method to overcome the limitations of ROS. Finally, we demonstrate the efficiency and reliability of our algorithm over ORB-SLAM3 in several experiments on both public and self-recorded datasets.

Original languageEnglish
Title of host publicationProceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023) - Volume IV
EditorsYi Qu, Mancang Gu, Yifeng Niu, Wenxing Fu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages392-401
Number of pages10
ISBN (Print)9789819710904
DOIs
StatePublished - 2024
Event3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023 - Nanjing, China
Duration: 9 Sep 202311 Sep 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1174 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023
Country/TerritoryChina
CityNanjing
Period9/09/2311/09/23

Keywords

  • centralied ternimal
  • UAV
  • VFC
  • visual and inertial

Fingerprint

Dive into the research topics of 'The Multi-UAV Collaborative Localization Based on Visual and Inertial Sensors'. Together they form a unique fingerprint.

Cite this