Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks

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.

View at publisher (open access)

Abstract

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.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are 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:

115 since deposited on 10 Feb 2013
9 in the past twelve months

Full-text downloads displays 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.

ID Code: 57023
Item Type: Conference Paper
Refereed: Yes
ISBN: 9780956533319
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 The International Council of the Aeronautical Sciences (ICAS)
Deposited On: 10 Feb 2013 23:16
Last Modified: 20 Mar 2013 20:17

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page