Three-dimensional optimal path planning for waypoint guidance of an autonomous underwater vehicle

2015 ◽  
Vol 67 ◽  
pp. 23-32 ◽  
Author(s):  
Mansour Ataei ◽  
Aghil Yousefi-Koma
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Optimal Path ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Optimal Path Planning

Autonomous underwater vehicle optimal path planning method for seabed terrain matching navigation

2017 ◽  
Vol 133 ◽  
pp. 107-115 ◽  
Author(s):  
Ye Li ◽  
Teng Ma ◽  
Pengyun Chen ◽  
Yanqing Jiang ◽  
Rupeng Wang ◽  
...  
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Optimal Path ◽  
Underwater Vehicle ◽  
Planning Method ◽  
Optimal Path Planning ◽  
Terrain Matching

Multicriterion Offline Path Planning of a Biomimetic Underwater Vehicle Using NSGA II

2010 ◽  
Author(s):  
Mansour Ataei ◽  
Aghil Yousefi-Koma ◽  
Masoud Shariat Panahi
Keyword(s):  
Path Planning ◽  
Pareto Front ◽  
Optimal Path ◽  
Underwater Vehicle ◽  
Pareto Optimal Solutions ◽  
Freedom Of Choice ◽  
Nsga Ii ◽  
Optimal Path Planning ◽  
Ga Algorithm ◽  
Margin Of Safety

In this paper an optimal 3-D path is generated offline for a Biomimetic Underwater Vehicle (BUV). The BUV swims forward by oscillating its body, turns by curving its body and dives by bending its head. The BUV is intended to systematically plan its path having only the initial and final points and the positions and dimensions of the obstacles. The four widely-accepted criteria of the optimal path planning of the BUV are “overall path length”, “margin of safety”, “smoothness of planar motion” and “gradient of dive”. In this study the multi-objective GA algorithm NSGA-II is employed to find a set of Pareto-optimal solutions where each solution represents a path that cannot be outrun by any other path considering all four criteria. The solution set, also called the Pareto front, gives the designer the freedom of choice when it comes to prioritizing various criteria.

Three-dimensional time-optimal path planning in the ocean

2020 ◽  
Vol 152 ◽  
pp. 101644 ◽  
Author(s):  
Chinmay S. Kulkarni ◽  
Pierre F.J. Lermusiaux
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Three Dimensional ◽  
Optimal Path Planning ◽  
Time Optimal

Three Dimensional Path Planning of Autonomous Underwater Vehicles

2013 ◽  
Vol 328 ◽  
pp. 128-132
Author(s):  
Yan Peng ◽  
Wei Qing Wu ◽  
Mei Liu ◽  
Shao Rong Xie ◽  
Jun Luo
Keyword(s):  
Lyapunov Function ◽  
Path Planning ◽  
Real Time ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Control Lyapunov Function

The path planning relates to the safe movement and navigation of the Autonomous Underwater Vehicles (AUV). This paper discusses the way of real-time path planning for autonomous underwater vehicle based on tracking control lyapunov function. The simulation conducted on H300 illustrates the effectiveness of proposed method.

Water wave optimization algorithm for autonomous underwater vehicle path planning problem

2021 ◽  
pp. 1-15
Author(s):  
Zheping Yan ◽  
Jinzhong Zhang ◽  
Jia Zeng ◽  
Jialing Tang
Keyword(s):  
Path Planning ◽  
Water Wave ◽  
Autonomous Underwater Vehicle ◽  
Optimal Path ◽  
Wave Theory ◽  
Underwater Vehicle ◽  
Local Optimum ◽  
Planning Problem ◽  
Vehicle Path ◽  
Path Planning Problem

In this paper, a water wave optimization (WWO) algorithm is proposed to solve the autonomous underwater vehicle (AUV) path planning problem to obtain an optimal or near-optimal path in the marine environment. Path planning is a prerequisite for the realization of submarine reconnaissance, surveillance, combat and other underwater tasks. The WWO algorithm based on shallow wave theory is a novel evolutionary algorithm that mimics wave motions containing propagation, refraction and breaking to obtain the global optimization solution. The WWO algorithm not only avoids jumps out of the local optimum and premature convergence but also has a faster convergence speed and higher calculation accuracy. To verify the effectiveness and feasibility, the WWO algorithm is applied to solve the randomly generated threat areas and generated fixed threat areas. Compared with other algorithms, the WWO algorithm can effectively balance exploration and exploitation to avoid threat areas and reach the intended target with minimum fuel costs. The experimental results demonstrate that the WWO algorithm has better optimization performance and is robust.

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