.png){kind=icon}
返回
UCAV Path Planning for Avoiding Obstacles using Cooperative Co-evolution Spider Monkey Optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.knosys.2022.108713.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The unmanned combat aerial vehicle (UCAV) path planning problem is a complex global optimization problem that aims to seek an optimal flight route that avoids the threats and constraints on the battlefield. However, as the number and degree of the path threats increases, the recent UCAV path planning algorithms all suffer from being trapped into local optima with a low convergence rate, which leads to the poor performance. Therefore, to resolve these problems, we propose a Cooperative co-Evolution (CE)-based Spider Monkey Optimization (SMO) algorithm, named CESMO to address UCAV path planning problem for avoiding obstacles. First, a cooperative co-evolution strategy is proposed to prevent the algorithms from falling into local optima easily, enhancing the coherence of the path. After that, a further division is applied to the algorithm for diversifying the search direction of each individual in the sub-groups. Finally, the spider monkey optimization-based search mechanism is designed to further strengthen the search efficiency and boost the convergence rate. Experimental results demonstrate that our proposed method is more competitive than other state-of-the-art evolutionary algorithms for UCAV path planning problem considering the quality and stability of the final paths. (C)2022 Elsevier B.V. All rights reserved.
Keyword:
Unmanned combat aerial vehicle
Path planning
Spider monkey optimization
Cooperative co-evolution
期刊
K
IF:
7.6
论文数:
1.2W
被引数:
4.5W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏A constrained differential evolution algorithm to solve UAV path planning in disaster scenarios一种求解灾害场景下无人机路径规划的约束差分进化算法
PREAI
分享收藏
分享收藏
查看更多内容