A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

Author:

Wang Gaige12,Guo Lihong1,Duan Hong3,Wang Heqi1,Liu Luo12,Shao Mingzhen12

Affiliation:

1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

2. Graduate School of Chinese Academy of Sciences, Beijing 100039, China

3. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China

Abstract

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

Funder

State Key Laboratory of Laser Interaction with Material Research Fund

Publisher

Hindawi Limited

Subject

General Environmental Science,General Biochemistry, Genetics and Molecular Biology,General Medicine

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