Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning

The development of autonomous unmanned aerial vehicles (UAVs) is of high interest to many governmental and military organizations around the world. An essential aspect of UAV autonomy is the ability for automatic path planning. In this paper, we use the genetic algorithm (GA) and the particle swarm...

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Veröffentlicht in:	IEEE transactions on industrial informatics Jg. 9; H. 1; S. 132 - 141
Hauptverfasser:	Roberge, V., Tarbouchi, M., Labonte, G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.02.2013 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Cost function Fuels Genetic algorithm (GA) Genetic algorithms Optimization parallel computing particle swarm optimization (PSO) Path planning Real time Studies Three dimensional displays Trajectories Trajectory Unmanned aerial vehicles unmanned aerial vehicles (UAVs)
ISSN:	1551-3203, 1941-0050
Online-Zugang:	Volltext
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