article · 2009

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

DongSeop Lee, Jacques Périaux, Felipé Gonzalez

Cited by 0Abstract and details only

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 Bezier 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.

Cite this paper

APA 7

Lee, D., Périaux, J., & Gonzalez, F. (2009). UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - another copy.

MLA 9

Lee, DongSeop, et al. “UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - another copy.” 2009.

Chicago

Lee, DongSeop, Jacques Périaux, and Felipé Gonzalez. 2009. “UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - another copy.”

Harvard

Lee, D., Périaux, J. and Gonzalez, F. (2009) ‘UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - another copy’.

BibTeX

@article{lee2009mission,
  title = {{UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - another copy}},
  author = {Lee, DongSeop and Périaux, Jacques and Gonzalez, Felipé},
  year = {2009}
}

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