학술논문

Hybrid Form of Particle Swarm Optimization and Genetic Algorithm For Optimal Path Planning in Coverage Mission by Cooperated Unmanned Aerial Vehicles
Document Type
article
Source
Journal of Aerospace Technology and Management. January 2020 12
Subject
Hybrid algorithm
Path planning
Evolutionary method
Multiple UAVs
Optimal patrolling
Cooperated control
Language
English
ISSN
2175-9146
Abstract
In this paper, a new form of open traveling salesman problem (OTSP) is used for path planning for optimal coverage of a wide area by cooperated unmanned aerial vehicles (UAVs). A hybrid form of particle swarm optimization (PSO) and genetic algorithm (GA) is developed for the current path planning problem of multiple UAVs in the coverage mission. Three path-planning approaches are introduced through a group of the waypoints in a mission area: PSO, genetic algorithm, and a hybrid form of parallel PSO-genetic algorithm. The proposed hybrid optimization tries to integrate the advantages of the PSO, i.e. coming out from local minimal, and genetic algorithm, i.e. better quality solutions within a reasonable computational time. These three approached are compared in many scenarios with different levels of difficulty. Statistical analyses reveal that the hybrid algorithm is a more effective strategy than others for the mentioned problem.