基于改进PSO-Lévy算法的海流环境下AUV节能路径规划

杨惠珍; 王子江; 周卓彧; 杨钧; 李建国

doi:10.11993/j.issn.2096-3920.2023-0062

基于改进PSO-Lévy算法的海流环境下AUV节能路径规划

doi: 10.11993/j.issn.2096-3920.2023-0062

杨惠珍^{1, 2,},
王子江^{1, 2,},
周卓彧^{1, 2,},
杨钧^{1, 2,},
李建国^{1, 2,}

1.
西北工业大学航海学院, 陕西西安, 710072
2.
水下信息与控制技术全国重点实验室, 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(2021-JCJQ-LB-030-03).

详细信息

作者简介:
杨惠珍(1974-), 女, 博士, 副教授, 主要研究方向为水下机器人控制与仿真、多机器人系统

中图分类号: TJ630.1; TP29
计量
- 文章访问数: 33
- HTML全文浏览量: 1
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2023-05-17
- 修回日期: 2023-09-11
- 录用日期: 2023-09-18
- 网络出版日期: 2024-01-31

Energy-optimal Path Planning for AUV under Ocean Current Environment Based on Improved PSO-Lévy algorithm

YANG Huizhen^{1, 2
,},
WANG Zijiang^{1, 2
,},
ZHOU Zhuoyu^{1, 2
,},
YANG Jun^{1, 2
,},
LI Jianguo^{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: 为了获取海流环境中自主水下航行器(AUV)的节能避障路径, 建立了包含海流场速度信息、水下地形障碍的三维动态海流环境模型; 基于航行能耗、AUV机动性能约束和障碍物约束, 建立增广目标函数, 提出了一种基于权重调节机制和随机游走特性的改进PSO-Lévy算法。将基于最佳阻尼比的参数调节策略和基于Lévy-flight过程的步长随机游走策略引入PSO算法, 通过概率执行粒子大步长游走操作以及对粒子惯性速度进行调控, 弥补了PSO步长短、跳出局部最优能力弱的劣势。仿真结果表明, 所提出的算法能在有效避开障碍物的同时利用海流信息规划出低能耗的最优路径。
- 自主水下航行器 /
- 动态海流 /
- 路径规划 /
- 能量消耗
Abstract: To obtain energy-efficient obstacle avoidance paths of autonomous underwater vehicle (autonomous underwater vehicle, AUV) in dynamic current environment. A three-dimensional dynamic ocean current environment model based on dynamic current velocity field and underwater topographic obstacles was established. The objective function for optimal energy consumption based on kinematic constraint and the obstacle constraint is established. An improved particle-swarm-optimization-Lévy (PSO-Lévy) algorithm based on weight adjustment mechanism and random wandering mechanism is proposed. By executing long-step random walk operation and regulating the velocity of particles with certain probability, the improved algorithm can get longer step and jump out of local optimum. Simulation results show that the proposed method can plan the optimal path with low energy consumption and short distance, and can effectively ensure path safety and displaying higher efficiency.
- autonomous underwater vehicles /
- dynamic current /
- path planning /
- energy consumption

HTML全文

图 1 基于水下山峰障碍物和叠加Lamb涡三维环境图

Figure 1. Three-dimensional environment map based on mountain peaks and Lamb vortex

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图 2 改进的PSO-Lévy算法流程框图

Figure 2. Flow chart of improved PSO-Lévy algorithm

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图 3 三维动态海流环境中PSO规划结果

Figure 3. Simulation results for PSO in 3D dynamic current environment

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图 4 三维动态海流环境中APF-APSO规划结果

Figure 4. Simulation results for APF-APSO in 3D dynamic current environment

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图 5 三维动态海流环境中PSO-Lévy规划结果

Figure 5. Simulation results for PSO-Lévy in 3D dynamic current environment

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图 6 三维环境路径规划能耗变化图

Figure 6. Variation map of energy consumption in 3D environment

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图 7 航行过程中的航向角

Figure 7. course angle during navigation

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图 8 航行过程中的俯仰角

Figure 8. pitch angle during navigation

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图 9 三维动态海流环境中算法对比结果

Figure 9. Comparison results for algorithms in 3D dynamic current environment

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