On-board multi-objective mission planning for unmanned aerial vehicles

Wu, Paul P.Y., Campbell, Duncan A., & Merz, Torsten (2009) On-board multi-objective mission planning for unmanned aerial vehicles. In IEEE Aerospace Conference, 7-14 March 2009, Big Sky, Montana.

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A system for automated mission planning is presented with a view to operate Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). This paper describes methods for modelling decision variables, for enroute flight planning under Visual Flight Rules (VFR). For demonstration purposes, the task of delivering a medical package to a remote location was chosen. Decision variables include fuel consumption, flight time, wind and weather conditions, terrain elevation, airspace classification and the flight trajectories of other aircraft. The decision variables are transformed, using a Multi-Criteria Decision Making (MCDM) cost function, into a single cost value for a grid-based search algorithm (e.g. A*). It is shown that the proposed system provides a means for fast, autonomous generation of near-optimal flight plans, which in turn are a key enabler in the operation of UAVs in the NAS.

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11 citations in Scopus
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ID Code: 20341
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: path planning, multi-criteria decision making, unmanned aerial vehicles (UAV), uncertainty, probability density field
DOI: 10.1109/AERO.2009.4839608
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerospace Engineering not elsewhere classified (090199)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
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 2009 IEEE
Deposited On: 06 May 2009 00:41
Last Modified: 29 Feb 2012 13:59

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