QUT ePrints

UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser

Lee, Dong-Seop, Periaux, Jacques , & Gonzalez, Luis F. (2009) UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser. In Anderson, K. & Flowers, G. (Eds.) Proceedings of 2009 Design Engineering Technical Conferences & Computers and Information in Engineering Conference, American Society of Mechanical Engineers (ASME), San Diego Convention Center, San Diego, Califorina , pp. 1-10.

[img] Published Version (PDF 1MB)
Administrators only | Request a copy from author

    View at publisher

    Abstract

    This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

    Impact and interest:

    1 citations in Web of Science®
    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.

    ID Code: 33029
    Item Type: Conference Paper
    Additional URLs:
    Keywords: Unmanned Aerial Systems, Path Planning, Hybrid Optimiser
    DOI: 10.1115/1.4001336
    ISBN: 9780791838563
    Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerodynamics (excl. Hypersonic Aerodynamics) (090101)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
    Australian and New Zealand Standard Research Classification > TECHNOLOGY (100000) > AGRICULTURAL BIOTECHNOLOGY (100100) > Agricultural Molecular Engineering of Nucleic Acids and Proteins (100103)
    Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > Schools > School of Engineering Systems
    Copyright Owner: Copyright 2010 American Society of Mechanical Engineers
    Deposited On: 07 Jul 2010 08:14
    Last Modified: 11 Aug 2011 02:49

    Export: EndNote | Dublin Core | BibTeX

    Repository Staff Only: item control page