UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser
Contribuinte(s) |
Anderson, K. Flowers, G. |
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Data(s) |
2009
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Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Publicador |
ASME International |
Relação |
http://eprints.qut.edu.au/33029/1/c33029.pdf DOI:10.1115/1.4001336 Lee, Dong-Seop, Periaux, Jacques, & Gonzalez, Luis F. (2009) UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser. Journal of Dynamic Systems, Measurement, and Control, 132(4), pp. 1-10. |
Direitos |
Copyright 2010 American Society of Mechanical Engineers |
Fonte |
Faculty of Built Environment and Engineering; School of Engineering Systems |
Palavras-Chave | #090101 Aerodynamics (excl. Hypersonic Aerodynamics) #090104 Aircraft Performance and Flight Control Systems #100103 Agricultural Molecular Engineering of Nucleic Acids and Proteins #Unmanned Aerial Systems #Path Planning #Hybrid Optimiser |
Tipo |
Journal Article |