Survey of deep learning for autonomous surface vehicles in marine environments

Y Qiao, J Yin, W Wang, F Duarte… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Within the next several years, there will be a high level of autonomous technology that will
be available for widespread use, which will reduce labor costs, increase safety, save energy …

Cooperative USV–UAV marine search and rescue with visual navigation and reinforcement learning-based control

Y Wang, W Liu, J Liu, C Sun - ISA transactions, 2023 - Elsevier
This paper investigates visual navigation and control of a cooperative unmanned surface
vehicle (USV)-unmanned aerial vehicle (UAV) system for marine search and rescue. First, a …

Event-triggered adaptive neural fault-tolerant control of underactuated MSVs with input saturation

G Zhu, Y Ma, Z Li, R Malekian… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper investigates the tracking control problem of marine surface vessels (MSVs) in the
presence of uncertain dynamics and external disturbances. The facts that actuators are …

USV formation and path-following control via deep reinforcement learning with random braking

Y Zhao, Y Ma, S Hu - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
This article addresses the problem of path following for underactuated unmanned surface
vessels (USVs) formation via a modified deep reinforcement learning with random braking …

[Retracted] Deep Reinforcement Learning‐Based Path Control and Optimization for Unmanned Ships

D Wu, Y Lei, M He, C Zhang, L Ji - … and Mobile Computing, 2022 - Wiley Online Library
Unmanned ship navigates on the water in an autonomous or semiautonomous way, which
can be widely used in maritime transportation, intelligence collection, maritime training and …

Safe-critical formation reconfiguration of multiple unmanned surface vehicles subject to static and dynamic obstacles based on guiding vector fields and fixed-time …

X Gong, L Liu, Z Peng - Ocean Engineering, 2022 - Elsevier
This paper addresses the formation reconfiguration problem of multiple unmanned surface
vehicles subject to static and dynamic obstacles. Specifically, a desired heading is …

Safe deep reinforcement learning-based adaptive control for USV interception mission

B Du, B Lin, C Zhang, B Dong, W Zhang - Ocean Engineering, 2022 - Elsevier
This paper aims to develop a safe learning scheme of the USV interception mission. A safe
Lyapunov boundary deep deterministic policy gradient (SLDDPG) algorithm is presented for …

An improved stanley guidance law for large curvature path following of unmanned surface vehicle

X Yang, X Yan, W Liu, H Ye, Z Du, W Zhong - Ocean Engineering, 2022 - Elsevier
In order to enhance the large curvature path following performance of unmanned surface
vehicle (USV), an improved Stanley guidance law (ISGL) is proposed. To the best of our …

Data-driven distributed formation control of under-actuated unmanned surface vehicles with collision avoidance via model-based deep reinforcement learning

C Pan, Z Peng, L Liu, D Wang - Ocean engineering, 2023 - Elsevier
This paper addresses the distributed formation control with collision avoidance for multiple
under-actuated unmanned surface vehicles (USVs) subject to fully unknown models. A fully …

Event-triggered asymptotic tracking control of underactuated ships with prescribed performance

Y Deng, Z Zhang, M Gong, T Ni - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Adapting to the navigational high-precision tracking tasks, this paper develops an event-
triggered adaptive neural asymptotic tracking control framework for underactuated ships …