Docking assessment algorithm for autonomous underwater vehicles

被引:22
|
作者
Mai The Vu [1 ]
Choi, Hyeung-Sik [2 ]
Thieu Quang Minh Nhat [3 ]
Ngoc Duc Nguyen [4 ]
Lee, Sang-Do [5 ]
Tat-Hien Le [6 ]
Sur, Joono [7 ]
机构
[1] Sejong Univ, Sch Intelligent Mechatron Engn, 98 Gunja Dong, Seoul 143747, South Korea
[2] Korea Maritime & Ocean Univ, Div Mech Engn, 727 Taejong Ro, Busan 49112, South Korea
[3] Renesas Design Vietnam Co Ltd, Dist 7, Ho Chi Minh City, Vietnam
[4] Seoul Natl Univ Sci & Technol, Dept Elect & Informat Engn, Seoul 01811, South Korea
[5] Mokpo Natl Maritime Univ, Div Nav & Informat Syst, 91 Haedanghak Ro, Mokpo 58628, South Korea
[6] Ho Chi Minh City Univ Technol, VNU HCM, Ho Chi Minh City, Vietnam
[7] Korea Maritime & Ocean Univ, Marine Unmanned Syst Ctr, 727 Taejong Ro, Busan 49112, South Korea
关键词
Autonomous Underwater Vehicle (AUV); Docking; Neural Network (NN); Making Decision; Simulation; CONSTRUCTION ROBOT; AUV; OPERATION; DESIGN;
D O I
10.1016/j.apor.2020.102180
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This paper presents an algorithm for docking a torpedo-shaped autonomous underwater vehicle (AUV). We propose a new docking assessment algorithm comprising three phases: depth tracking, docking-feasibility region analysis, and docking-success probability evaluation. For depth-tracking analysis, a neural network-generated path is used to satisfy constrained docking conditions of depth and distance. With regard to docking feasibility region analysis, the working space of the AUV can provide a possibility region of successful docking. In the analysis, working space is expressed by a turning ellipsoid, which is the numerical solution of the maximum yawing motion. An algorithm is presented to evaluate the probability of docking success, based on the probability of sensor data. A good contribution of this approach is that a criterion for assessing the feasibility of the desired path for docking is given through the proposed docking assessment algorithm.
引用
收藏
页数:14
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