UAVs path planning using particle swarm optimization

Abstract

Optimization is one of the important categories of engineering problems, concerned with the search for better solutions of maximum or minimum ways in a certain areas. Because of its complexity, the meta-heuristique algorithms are usually used and applied because these algorithms don't require prior knowledge of the search space and because they also depend on theories based on randomness. A large group of this algorithms (optimization techniques) compete to nd a better solution, the most prominent of which is particle swarm optimization (PSO), and given its good performance in many optimization problems, it is considered a modern method and is relatively close to experimenting with swarms. This thesis aims to provide a review and discussion of the application of the PSO algorithm and its projection to plan the path of drone swarms and we analyze its present situation of research and parameter selection, topology structure, Basic PSO algorithm and multi-objective optimization PSO and its simulations. Finally, current problems are analyzed and future research directions are presented.