Local path planning method of underwater glider considering obstacle avoidance

YU Wenju; DING Junhang; GUAN Sheng; WANG Yanfeng

doi:10.13873/J.1000-9787(2020)09-0060-03

Chinese

您当前的位置：

首页 >

文章列表页 >

Local path planning method of underwater glider considering obstacle avoidance

更新时间：2025-09-11

- Local path planning method of underwater glider considering obstacle avoidance
- Vol. 39, Issue 9, Pages: 60-62+65(2020)
- 作者机构：
  
  1. 青岛大学自动化学院
  2. 山东省生态纺织协同创新中心
  3. 山东省工业控制技术重点实验室
  4. 自然资源部第一海洋研究所
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)09-0060-03
  CLC： TP242
- Published：2020
- 稿件说明：
移动端阅览
[1]于文举,丁军航,官晟,王岩峰.考虑障碍物避让的水下滑翔机局部路径规划方法[J].传感器与微系统,2020,39(09):60-62+65.

YU Wenju, DING Junhang, GUAN Sheng, et al. Local path planning method of underwater glider considering obstacle avoidance[J]. 2020, 39(9): 60-62+65.
[1]于文举,丁军航,官晟,王岩峰.考虑障碍物避让的水下滑翔机局部路径规划方法[J].传感器与微系统,2020,39(09):60-62+65. DOI： 10.13873/J.1000-9787(2020)09-0060-03.

YU Wenju, DING Junhang, GUAN Sheng, et al. Local path planning method of underwater glider considering obstacle avoidance[J]. 2020, 39(9): 60-62+65. DOI： 10.13873/J.1000-9787(2020)09-0060-03.

摘要

针对水下滑翔机"V"形轨迹的周期性运动特点

提出一种适用于水下滑翔机在三维路径中避让障碍物的粒子群优化（PSO）算法。根据水下滑翔机的运动特征

给出水下工作环境的三维空间建模方法。结合水下滑翔机能耗问题

选择用规划路径的长度、障碍物的危险度和路径平滑度来制定适应度函数。提出一种惯性权重的非线性动态调整策略

提高了算法的全局搜寻能力。将优化后的算法与基本粒子群算法比较

结果表明:优化后的算法可以生成质量更高的路径

并且可以在更少的迭代次数下收敛到全局最优

有效地提高了粒子群算法应用在水下滑翔机路径规划的算法速度和能耗效率。

Abstract

Aiming at periodic motion characteristics of"V "trajectory of underwater glider

a particle swarm optimization（ PSO） algorithm is proposed to avoid obstacles in the three-dimensional path of underwater glider.Firstly

according to the motion characteristics of underwater glider

a three-dimensional space modeling method of underwater working environment is proposed. Then

combined with the energy consumption problem of the underwater glider

the fitness function is formulated by the length of the planned path

the danger degree of the obstacles and the smoothness of the path. Finally

a nonlinear dynamic adjustment strategy of inertia weight is proposed to improve the global search ability of the algorithm. Comparing the optimized algorithm with the basic PSO algorithm

the results show that the optimized algorithm can generate higher-quality paths and can converge to the global optimum in fewer iterations

effectively improve algorithm speed and energy consumption efficiency of PSO algorithm applied in underwater glider path planning.

关键词

Keywords

references

基于改进人工势场法的水下滑翔机路径规划 [J]. 李沛伦,杨启. 舰船科学技术 . 2019(07)

水下滑翔机稳态螺旋运动的时空尺度分析 [J]. 于鹏垚,沈聪,甄春博,王天霖. 舰船科学技术 . 2019(01)

水下滑翔机技术发展现状与展望 [J]. 沈新蕊,王延辉,杨绍琼,梁岩,李昊璋. 水下无人系统学报 . 2018(02)

基于改进粒子群算法的移动机器人路径规划 [J]. 王慧,王光宇,潘德文. 传感器与微系统 . 2017(05)

基于优化粒子群算法的无人机航路规划 [J]. 张建南,刘以安,王刚. 传感器与微系统 . 2017(03)

改进蚁群算法的飞机冲突解脱路径规划方法 [J]. 倪壮,肖刚,敬忠良,李旻哲. 传感器与微系统 . 2016(04)

基于自适应惯性权重的均值粒子群优化算法 [J]. 赵志刚,林玉娇,尹兆远. 计算机工程与科学 . 2016(03)

基于A * 算法的空间机械臂避障路径规划 [J]. 贾庆轩,陈钢,孙汉旭,郑双奇. 机械工程学报 . 2010(13)

水下滑翔机器人运动分析与载体设计 [J]. 张奇峰,俞建成,唐元贵,李硕,张艾群. 海洋工程 . 2006(01)

一种动态改变惯性权的自适应粒子群算法 [J]. 张选平,杜玉平,秦国强,覃征. 西安交通大学学报 . 2005(10)

粒子群优化算法综述 [J]. 杨维,李歧强. 中国工程科学 . 2004(05)

Views

195

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

MPPT control strategy for PV generation system based on improved PSO algorithm

Multi-swarm PSO algorithm based on parallel structure

Series fault arc identification method based on BP neural network optimized by PSO

Related Author

SUN Kai

LIU Guangyu

ZHANG Tianjia

YANG Yongsheng

ZHANG Yang

LIU Yan-li

Related Institution

School of Automation Engineering,Hangzhou Dianzi University

School of Aeronautics and Astronautics,Shanghai Jiao Tong University

College of Electrical and Control Engineering,Liaoning Technical University

⁰