Three dimensional D∗Lite path planning for Autonomous Underwater Vehicle under partly unknown environment

Author(s):  
Bing Sun ◽  
Daqi Zhu
2013 ◽  
Vol 328 ◽  
pp. 128-132
Author(s):  
Yan Peng ◽  
Wei Qing Wu ◽  
Mei Liu ◽  
Shao Rong Xie ◽  
Jun Luo

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.


2019 ◽  
Vol 52 (21) ◽  
pp. 315-322 ◽  
Author(s):  
Hui Sheng Lim ◽  
Shuangshuang Fan ◽  
Christopher K.H. Chin ◽  
Shuhong Chai ◽  
Neil Bose ◽  
...  

2017 ◽  
Vol 71 (2) ◽  
pp. 482-496 ◽  
Author(s):  
Daqi Zhu ◽  
Yu Liu ◽  
Bing Sun

For multi-Autonomous Underwater Vehicle (multi-AUV) system task assignment and path planning, a novel Glasius Bio-inspired Self-Organising Map (GBSOM) neural networks algorithm is proposed to solve relevant problems in a Three-Dimensional (3D) grid map. Firstly, a 3D Glasius Bio-inspired Neural Network (GBNN) model is established to represent the 3D underwater working environment. Using this model, the strength of neural activity is calculated at each node within the GBNN. Secondly, a Self-Organising Map (SOM) neural network is used to assign the targets to a set of AUVs and determine the order of the AUVs to access the target point. Finally, according to the magnitude of the neuron activity in the GBNN, the next AUV target point can be autonomously planned when the task assignment is completed. By repeating the above three steps, access to all target points is completed. Simulation and comparison studies are presented to demonstrate that the proposed algorithm can overcome the speed jump problem of SOM algorithms and path planning in the 3D underwater environments with static or dynamic obstacles.


Author(s):  
Mohammad Saghafi ◽  
Roham Lavimi

In this research, the flow around the autonomous underwater vehicles with symmetrical bodies is numerically investigated. Increasing the drag force in autonomous underwater vehicles increases the energy consumption and decreases the duration of underwater exploration and operations. Therefore, the main objective of this research is to decrease drag force with the change in geometry to reduce energy consumption. In this study, the decreasing or increasing trends of the drag force of axisymmetric bare hulls have been studied by making alterations in the curve equations and creating the optimal geometric shapes in terms of hydrodynamics for the noses and tails of autonomous underwater vehicles. The incompressible, three-dimensional, and steady Navier–Stokes equations have been used to simulate the flow. Also, k-ε Realizable with enhanced wall treatment was used for turbulence modeling. Validation results were acceptable with respect to the 3.6% and 1.4% difference with numerical and experimental results. The results showed that all the autonomous underwater vehicle hulls designed in this study, at an attack angle of 0°, had a lower drag force than the autonomous underwater vehicle hull used for validation except geometry no. 1. In addition, nose no. 3 has been selected as the best nose according to the lowest value of stagnation pressure, and also tail no. 3 has been chosen as the best tail due to the production of the lowest vortex. Therefore, geometry no. 5 has been designed using nose and tail no. 3. The comparison made here showed that the maximum drag reduction in geometry no. 5 was equal to 26%, and therefore, it has been selected as the best bare hull in terms of hydrodynamics.


2018 ◽  
Vol 51 (29) ◽  
pp. 323-328 ◽  
Author(s):  
Ayushman Barua ◽  
Jörg Kalwa ◽  
Yuri Shardt ◽  
Thomas Glotzbach

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