分布式多AUV协同搜索方法

doi:10.12305/j.issn.1001-506X.2022.05.29

摘要/Abstract

摘要：

针对水下协同搜索中存在通信延时、单个自主式水下航行器(autonomous underwater vehicle, AUV)易失效的问题, 提出一种采用分布式协同结构和滚动优化策略, 利用改进型头脑风暴优化(brain storm optimization, BSO)算法优化基于目标存在概率、环境不确定度、协调信息素的目标函数的新方法。仿真结果表明, 所提方法能实现避碰, 并在通信延时情况下仍有能力搜索到所有目标。通过仿真给出了所提方法关键参数的建议取值范围, 并验证了个别AUV在搜索过程中失效对总体搜索效果影响不大, 方法具有很强的实时性和鲁棒性。

关键词: 自主式水下航行器, 协同搜索, 协调信息素, 改进型头脑风暴优化算法

Abstract:

Aiming at the problems of communication delay and easy failure of a single autonomous underwater vehicle (AUV) in underwater cooperative search, a new method using distributed cooperative structure and rolling optimization strategy is proposed, which optimizes the objective function based on target existence probability, environmental uncertainty and coordinative pheromone by using the improved brain storm optimization(BSO) algorithm. Simulation results show that the proposed method can avoid collision and still be able to search all targets in the case of communication delay. Through simulation, the recommended value range of key parameters of the proposed method is given, and it is verified that the failure of individual AUV in the search process has little impact on the overall search effect, and the method has strong real-time and robustness.

Key words: autonomous underwater vehicle (AUV), cooperative search, coordination pheromone, improved brain storm optimization (BSO) algorithm

中图分类号:

TP249

高永琪, 马威强, 张林森, 王鹏, 赵苗. 分布式多AUV协同搜索方法[J]. 系统工程与电子技术, 2022, 44(5): 1670-1676.

Yongqi GAO, Weiqiang MA, Linsen ZHANG, Peng WANG, Miao ZHAO. Distributed multi-AUVs cooperative search method[J]. Systems Engineering and Electronics, 2022, 44(5): 1670-1676.

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参数符合	参数意义	值
p_d	传感器探测概率	0.96
p_f	传感器虚警概率	0.04
p₀	目标存在阈值	0.75
g_n	高斯分布峰值	0.324 8
σ²	高斯分布方差	0.49
τ	不确定度递减因子	0.1
M	充分大正数	1 000
H	较大协调信息素	5
L	较小协调信息素	1

算法	寻得目标数量/个	每步决策时间/s
GDBSO	8.80	0.704 0
BSO	8.24	0.924 9

子目标函数影响系数	寻得目标数量/个
k₁=0.2、k₂=0.6、k₃=0.2	8.38
k₁=0.3、k₂=0.5、k₃=0.2	8.60
k₁=0.4、k₂=0.4、k₃=0.2	8.80
k₁=0.5、k₂=0.3、k₃=0.2	8.58
k₁=0.6、k₂=0.2、k₃=0.2	8.46

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