Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6961666 | Advances in Engineering Software | 2016 | 16 Pages |
Abstract
Unmanned combat aerial vehicle (UCAV) path planning is a fairly complicated global optimum problem, which aims to obtain an optimal or near-optimal flight route with the threats and constraints in the combat field well considered. A new meta-heuristic grey wolf optimizer (GWO) is proposed to solve the UCAV two-dimension path planning problem. Then, the UCAV can find the safe path by connecting the chosen nodes of the two-dimensional coordinates while avoiding the threats areas and costing minimum fuel. Conducted simulations show that the proposed method is more competent for the UCAV path planning scheme than other state-of-the-art evolutionary algorithms considering the quality, speed, and stability of final solutions.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Software
Authors
Zhang Sen, Zhou Yongquan, Li Zhiming, Pan Wei,