A new path planning method for AUV based on the Navier-Stokes equations for ocean currents

被引:6
作者
Yan, Xinhui [1 ,2 ]
Wang, Wenke [3 ]
Huang, Chuangxia [1 ,2 ]
Li, Le [3 ]
机构
[1] Changsha Univ Sci & Technol, Sch Math & Stat, Changsha 410114, Hunan, Peoples R China
[2] Hunan Prov Key Lab Math Modeling & Anal Engn, Changsha 410114, Hunan, Peoples R China
[3] Natl Univ Def Technol, Sch Meteorol & Oceanog, Changsha 410114, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
AUV; Complex current environment; N-S equations; Artificial potential field; Path planning; AUTONOMOUS UNDERWATER VEHICLES; FIELD;
D O I
10.1016/j.matcom.2023.08.030
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The autonomous underwater vehicle (AUV), due to its flexibility, safety, and other characteristics, has been widely used in various marine applications such as underwater mapping, marine ecological monitoring and marine scientific. When navigating in complex and ever-changing ocean currents, one of the key challenges in AUV control is how to effectively avoid unknown obstacles such as sunken ships and reefs, and plan the route to reach the target point. In this paper, based on partially measured ocean current velocities, the Navier-Stokes equations (N-S equations) are used to characterize the ocean current velocities within a small-scale region. Furthermore, the improved artificial potential field method is used for path planning after integrating the velocity information. Simulation and experiments indicate that the proposed algorithm is better suited to complex marine environments. (c) 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:199 / 208
页数:10
相关论文
共 32 条
[1]   Evolutionary path planning for autonomous underwater vehicles in a variable ocean [J].
Alvarez, A ;
Caiti, A ;
Onken, R .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2004, 29 (02) :418-429
[2]   Intelligent Path Planning Technologies of Underwater Vehicles: a Review [J].
An, Dong ;
Mu, Yizhuo ;
Wang, Yaqian ;
Li, Baoke ;
Wei, Yaoguang .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2023, 107 (02)
[3]  
Anderson J.D., 2007, Computational Fluid Dynamics: The Basics with Applications
[4]  
BLIDBERG D.R., 2001, The development of autonomous underwater vehicles (AUV)
[5]  
a brief summary
[6]   Path planning for autonomous underwater vehicle in time-varying current [J].
Cao, Xiang ;
Sun, Chang-yin ;
Chen, Ming-zhi .
IET INTELLIGENT TRANSPORT SYSTEMS, 2019, 13 (08) :1265-1271
[7]  
Chen S., 2012, Global Path Planning for AUV Based on Sparse a* Search Algorithm
[8]  
Cheng CL, 2015, CAN CON EL COMP EN, P717, DOI 10.1109/CCECE.2015.7129363
[9]   Path planning and obstacle avoidance for AUV: A review [J].
Cheng, Chunxi ;
Sha, Qixin ;
He, Bo ;
Li, Guangliang .
OCEAN ENGINEERING, 2021, 235
[10]   Active obstacle avoidance method of autonomous vehicle based on improved artificial potential field [J].
Duan, Yijian ;
Yang, Changbo ;
Zhu, Jihong ;
Meng, Yanmei ;
Liu, Xin .
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2022, 19 (04)