面向辅助多AUV作业的USV路径规划研究

米彦龙; 杨惠珍; 郭天阳

doi:10.11993/j.issn.2096-3920.2025-0113

面向辅助多AUV作业的USV路径规划研究

doi: 10.11993/j.issn.2096-3920.2025-0113

米彦龙^{1, 2},
杨惠珍^{1, 2,},
郭天阳^{1, 2}

1.
西北工业大学航海学院, 陕西西安, 710072
2.
水下信息与控制全国重点实验室, 陕西西安, 710072

基金项目: 水下信息与控制全国重点实验室基金项目资助(2024-CXPT-GF-JJ-036-06).

详细信息

作者简介:
米彦龙(2000-), 男, 研究生在读, 主要研究方向为水下航行器路径规划

通讯作者:
杨惠珍(1974-), 女, 博士, 研究员, 主要研究方向为水下航行器路径规划.

中图分类号: TJ630; U663
计量
- 文章访问数: 27
- HTML全文浏览量: 15
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2025-08-25
- 修回日期: 2025-09-14
- 录用日期: 2025-09-26
- 网络出版日期: 2026-01-19

Research on USV path planning for assisted multi-AUVs navigation

MI Yanlong^{1, 2},
YANG Huizhen^{1, 2
,},
GUO Tianyang^{1, 2}

1.
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
2.
Underwater Information and Control Laboratory, Xi’an 710072, China

摘要

摘要: 面向无人水面艇(USV)辅助多自主水下航行器(AUV)作业应用背景, 提出一种基于超短基线定位系统(USBL)的USV-AUV多目标协同路径规划方法。通过分析USBL工作原理, 结合海洋水声信号传播特性, 由USBL信号的有效区、射线声学理论定义的声线传播边界及根据声呐方程计算出的最大作用距离共同构成协同作业的稳定通信范围。在确保USV-AUV保持在水声通信有效范围内的同时, 进一步优化路径长度、路径平滑度和USV-AUV的通信性能, 建立了USV-AUV协同路径规划的多目标优化模型, 利用改进遗传算法求解, 探究通信距离、AUV作业深度等参数对USV规划路径影响的仿真实验, 结果表明, 所提方法在满足USBL通信约束的前提下, 能够有效提升USV与AUV协同工作的稳定性, 为多AUV执行复杂海洋任务提供可靠保障。
- 无人水面艇-自主水下航行器协同 /
- 超短基线定位系统 /
- 路径规划
Abstract: In the context of USV-assisted multi-AUVs operations, this paper proposes a multi-objective collaborative path planning method for USV-AUVs systems based on the Ultra-Short Baseline Locating System (USBL). The working principle of the USBL is analysed, and combined with the acoustic signal propagation characteristics in marine environments, the stable communication range for collaborative operations is defined by the effective zone of the USBL signal, the acoustic ray propagation boundary defined by ray acoustics theory, and the maximum effective range calculated using the sonar equation. While ensuring that the USV and AUV remain within the effective range of acoustic communication, the method further optimises path length, path smoothness, and communication performance between the USV and AUV. A multi-objective optimisation model for USV-AUVs collaborative path planning is established, and an improved genetic algorithm is used to solve it. Simulation experiments are conducted to investigate the influence of parameters such as communication distance and AUV operational depth on the USV planning path. The results indicate that the proposed method can effectively enhance the stability of USV-AUVs collaborative operations while satisfying USBL communication constraints, providing a reliable foundation for multiple AUVs to execute complex marine missions.
- USV-AUVs collaboration /
- ultra-short baseline locating system /
- path planning

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图 1 工作场景示意图

Figure 1. Schematic diagram of the work scene

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图 2 USBL定位原理图

Figure 2. Schematic diagram of USBL positioning principle

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图 3 USV/AUV盲区相对位置图

Figure 3. Relative position of USV/AUV blind spots

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图 4 二维平面示意图

Figure 4. 2D Plane Schematic

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图 5 GA-PSO-TLBO算法流程图

Figure 5. GA-PSO-TLBO algorithm flowchart

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图 6 不同算法在仿真场景1中的规划结果

Figure 6. The planning results of different algorithms in simulation scenario 1

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图 7 不同算法在工作场景2中的规划结果

Figure 7. The planning results of different algorithms in work scenario 2

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图 8 权重系数变化对路径规划效果的影响

Figure 8. The impact of changes in weight coefficients on the effectiveness of path planning.

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表 1 不同高度差的路径规划结果

Table 1. Path planning results under different height differences

USV-AUV 高度差/m	GA			GA-PSO-TLBO
USV-AUV 高度差/m	路径长度/m	通信性能评估/%	USV 最大转角/(°)	路径长度/m	通信性能评估/%	USV 最大转角/(°)
100	1052	97.33	40.16	1052	97.33	40.40
150	1279	96.00	75.37	1130	96.67	75.20
200	1280	95.34	92.56	1203	96.33	66.07
250	1311	95.33	93.81	1211	95.50	103.60
300	1562	94.10	107.84	1431	94.40	103.53

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表 2 不同稳定通信距离的路径规划结果

Table 2. Path planning results for different stable communication distances

稳定通信距离/m	GA			GA-PSO-TLBO
稳定通信距离/m	路径长度/m	通信性能评估/%	USV 最大转角/(°)	路径长度/m	通信性能评估/100%	USV 最大转角/(°)
100	1050	79.74	40.24	1050	79.74	40.70
150	1280	82.98	72.79	1170	84.50	72.77
200	1280	89.29	93.44	1250	90.33	84.35
250	1310	93.13	90.98	1200	95.50	100.80
300	1660	94.99	111.10	1474	97.00	106.77

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