Journal
AEROSPACE SCIENCE AND TECHNOLOGY
Volume 16, Issue 1, Pages 47-55Publisher
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ast.2011.02.006
Keywords
Autonomous UAV; Voronoi diagram; Genetic algorithm; Path planning
Categories
Ask authors/readers for more resources
A new optimization algorithm called multi-frequency vibrational genetic algorithm (mVGA) that can be used to solve the path planning problems of autonomous unmanned aerial vehicles (UAVs) is significantly improved. The algorithm emphasizes a new mutation application strategy and diversity variety such as the global random and the local random diversity. Clustering method and Voronoi diagram concepts are used within the initial population phase of mVGA process. The new algorithm and three additional GAs in the literature are applied to the path planning problem in two different three-dimensional (3D) environments such as sinusoidal and city type terrain models, and their results are compared. For both of the demonstration problems considered, remarkable reductions in the computational times have been accomplished. (C) 2011 Elsevier Masson SAS. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available