QUT ePrints

Multi-sensor data fusion for UAV navigation during landing operations

Yang, Xilin, Mejias, Luis, & Garratt, Matt (2011) Multi-sensor data fusion for UAV navigation during landing operations. In ACRA 2011, Monash University, Melbourne, VIC. (In Press)

[img] Accepted Version (PDF 1029Kb)

    Abstract

    This paper presents a practical framework to syn- thesize multi-sensor navigation information for lo- calization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

    Citations:

    Search Google Scholar™

    Citation countsare sourced monthly from Scopus and Web of Science citation databases.

    These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.

    Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

    Full-text downloads:

    89 since deposited on 04 Dec 2011
    89 in the past twelve months

    Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

    More statistics...
    ID Code: 47449
    Item Type: Conference Paper
    Keywords: Unmanned Aerial Vehicles, Multi-sensor data fusion, Autonomous Landing
    Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
    Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
    Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > Schools > School of Engineering Systems
    Copyright Owner: Copyright 2011 The authors.
    Deposited On: 05 Dec 2011 09:21
    Last Modified: 06 Dec 2011 03:07

    Export: EndNote | Dublin Core | BibTeX

    Staff only: HERDC collection form

    Repository Staff Only: item control page