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Xi Lyu, Yushan Sun, Lifeng Wang, Jiehui Tan and Liwen Zhang
This study aims to solve the problems of sparse reward, single policy, and poor environmental adaptability in the local motion planning task of autonomous underwater vehicles (AUVs). We propose a two-layer deep deterministic policy gradient algorithm-bas...
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Guocheng Zhang, Jixiao Liu, Yushan Sun, Xiangrui Ran and Puxin Chai
This paper aims to focus on the path planning problem of AUV in the marine environment. As well as considering the path length and safe obstacle avoidance, ocean currents should not be ignored as the main factor affecting the navigation energy consumptio...
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Yushan Sun, Puxin Chai, Guocheng Zhang, Tian Zhou and Haotian Zheng
In the motion control of AUVs, especially those driven by multiple thrusters, the thruster misalignment and thrust loss cause the actual force and moment applied to the AUV to deviate from that desired, making accurate and fast motion control difficult. ...
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Yu Qi, Xinyu Wu, Guocheng Zhang and Yushan Sun
In order to improve the endurance of underwater vehicles and make it possible for the underwater vehicle to inspect long-distance water tunnels, a sliding mode control method based on event triggering is proposed for the depth control of underwater vehic...
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Gongxing Wu, Xiaolong Zhao, Yushan Sun and Linling Wang
The towing operation of multi-tug-assisted ship navigation mainly relies on the experience of the captain, and there is no set of effective operation methods. Therefore, it is difficult to achieve accurate assisted navigation when multiple tugboats work ...
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Yushan Sun, Xiaokun Luo, Xiangrui Ran and Guocheng Zhang
This research aims to solve the safe navigation problem of autonomous underwater vehicles (AUVs) in deep ocean, which is a complex and changeable environment with various mountains. When an AUV reaches the deep sea navigation, it encounters many underwat...
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Yushan Sun, Xiangrui Ran, Guocheng Zhang, Hao Xu and Xiangbin Wang
This study proposed the 3D path planning of an autonomous underwater vehicle (AUV) by using the hierarchical deep Q network (HDQN) combined with the prioritized experience replay. The path planning task was divided into three layers, which realized the d...
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Yushan Sun, Chenming Zhang, Guocheng Zhang, Hao Xu and Xiangrui Ran
In this paper, the three-dimensional (3D) path tracking control of an autonomous underwater vehicle (AUV) under the action of sea currents was researched. A novel reward function was proposed to improve learning ability and a disturbance observer was dev...
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