Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks
Contribuinte(s) |
Grant, Ian |
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Data(s) |
01/09/2012
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Resumo |
The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions. |
Formato |
application/pdf |
Identificador | |
Publicador |
Optimage Ltd. |
Relação |
http://eprints.qut.edu.au/57023/1/ICAS_2012_928.pdf http://www.icas.org/ICAS_ARCHIVE_CD1998-2010/ICAS2012/PAPERS/928.PDF Rappa, Giovani, Gonzalez, Luis F., Kok, Jonathan, & Quagliotti, Fulvia (2012) Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks. In Grant, Ian (Ed.) Proceedings of the 28th International Congress of the Aeronautical Sciences, Optimage Ltd., Brisbane Convention & Exhibition Centre, Brisbane, QLD, pp. 1-13. |
Direitos |
Copyright 2012 The International Council of the Aeronautical Sciences (ICAS) |
Fonte |
Australian Research Centre for Aerospace Automation; Science & Engineering Faculty |
Palavras-Chave | #090000 ENGINEERING |
Tipo |
Conference Paper |