Toward autonomous uav localization via aerial image registration

Xuezhi Wang, Allison Kealy, Wenchao Li, Beth Jelfs, Christopher Gilliam, Samantha Le May, Bill Moran

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Absolute localization of a flying UAV on its own in a global-navigation-satellite-system (GNSS)-denied environment is always a challenge. In this paper, we present a landmark-based approach where a UAV is automatically locked into the landmark scene shown in a georeferenced image via a feedback control loop, which is driven by the output of an aerial image registration. To pursue a real-time application, we design and implement a speeded-up-robust-features (SURF)-based image registration algorithm that focuses efficiency and robustness under a 2D geometric transformation. A linear UAV controller with signals of four degrees of freedom is derived from the estimated transformation matrix. The approach is validated in a virtual simulation environment, with experimental results demonstrating the effectiveness and robustness of the proposed UAV self-localization system.

Original languageEnglish
Article number435
Pages (from-to)1-15
Number of pages15
JournalElectronics (Switzerland)
Volume10
Issue number4
DOIs
Publication statusPublished - 2 Feb 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Image registration
  • Landmark detection
  • SURF
  • UAV control
  • UAV localization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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