During the implementation of time-consuming tasks such as underwater observation or detection, AUV has to face a difficult and urgent problem that its working duration is greatly shortened by the limited energy stored in the battery device. To solve the power problem, a docking station is installed underwater for AUV charging its battery. However, to realize the automatic underwater charging of AUV via a docking station, the accurate and efficient completion of underwater homing and docking is required for AUV. Underwater automatic homing and docking system is of great significance to improve work efficiency and prolong the endurance of AUV save cost. In this paper, a unified approach that involves such as task planning, guidance and control design, thrust allocation has been proposed to provide a complete solution to the problem of homing and docking of an over-actuated AUV. The task-based hybrid target point/line planning and following strategy are proposed for AUV homing and docking. At the beginning of homing, AUV is planned to follow a straight line via the line of sight (LoS) method. Afterward, AUV starts to follow multiple predefined target points until reaching the docking station. At the final stage of docking (within 10 m), a dedicated computer vision algorithm is applied to detect a newly designed LED light array fixed on the docking station to provide accurate guidance for the AUV to dock. The sliding mode control technique is used for the motion control of the AUV allowing robustness. As the AUV configured with eight thrusters is over-actuated, the problem of the thrust allocation is very important and successfully solved using the quadratic programming (QP) optimization method. Finally, the simulations of homing and docking tasks using the AUV are accomplished to verify the proposed approach.

The underwater wireless sensor network (UWSNs) is an important communication facility supporting underwater monitoring applications. However, the transmission channel has the characteristics of high bit error rate, strong multipath effect, and many interference factors, and the network node has the characteristics of high energy consumption, difficult energy supply, and the node position vulnerable to change, which makes it extremely difficult for UWSNs to realize the reliable and efficient packet forwarding. To address the problem, we propose the Stackelberg Q-learning based multi-hop cooperative routing algorithm (SQMCR). The SQMCR builds the transmission routes based on the Q-learning algorithm, considering factors such as the delay, the remaining energy, and the network topology, which improves the rationality and adaptability of selecting the next-hop node. By balancing the packet forwarding benefits and the energy consumption costs based on the Stackelberg Q-learning algorithm, the SQMCR establishes the cooperative communication policy to ensure both the reliability and efficiency of underwater communications. It also adopts initializing Q-values and dynamic exploration probabilities optimization methods to further improve the performance of routing algorithms. Experimental results show that the SQMCR can help UWSNs increase the packet forwarding reliability and prolong the network lifetime by 17%. It has a better environment and application adaptability and is more suitable for underwater high-reliability applications.

The underwater wireless sensor network is an important component of the underwater three-dimensional monitoring system. Due to the high bit error rate, high delay, low bandwidth, limited energy, and high dynamic of underwater networks, it is very difficult to realize efficient and reliable data transmission. Therefore, this paper posits that it is not enough to design the routing algorithm only from the perspective of the transmission environment; the comprehensive design of the data transmission algorithm should also be combined with the application. An edge prediction-based adaptive data transmission algorithm (EP-ADTA) is proposed that can dynamically adapt to the needs of underwater monitoring applications and the changes in the transmission environment. EP-ADTA uses the end–edge–cloud architecture to define the underwater wireless sensor networks. The algorithm uses communication nodes as the agents, realizes the monitoring data prediction and compression according to the edge prediction, dynamically selects the transmission route, and controls the data transmission accuracy based on reinforcement learning. The simulation results show that EP-ADTA can meet the accuracy requirements of underwater monitoring applications, dynamically adapt to the changes in the transmission environment, and ensure efficient and reliable data transmission in underwater wireless sensor networks.

Underwater target detection is a pivotal technology in marine observation. Traditional detection methods primarily rely on acoustic and optical techniques. However, their accuracy is constrained in turbid waters and complex environments. Inspired by weakly electric fish, we present a spatially sensitive detection system based on active electrosense, capable of autonomously generating electric fields to identify underwater targets. This system incorporates the concept of multi-measurement vectors (MMVs) from compressed sensing and the direction of arrival estimation problem, adapting it to our specific application by utilizing spatial geometric information for multi-electrode signal detection. This approach effectively enhances detection sensitivity in both short distance and turbid water environments. Experiments in a saltwater pool demonstrated the system’s excellent current sensitivity to metallic targets, such as submarine cables, particularly at short distances. This capability addresses inherent challenges in traditional optical and acoustic methods, highlighting the practicality and effectiveness of the proposed system.

The fall pipe rock dumping technique is extensively employed to create protection embankments around submarine cables, mitigating distortion and breakage resulting from bottom scouring. During the rock dumping operation, intricate interactions among the pipeline, rocks, and water currents can affect the stability and efficiency of the fall pipe system. This research proposed a method employing the fluid–structure interaction to analyze the interactions between the pipeline, rocks, and water currents. The paper begins with the design of an innovative fall pipe rock dumping system and presents a theoretical analysis of the applied model testing approach. The simulation parameters were determined according to the geometric, Froude, and Strouhal similarity criteria. A thorough numerical analysis was performed to investigate the hydrodynamic properties of the rockfall pipeline under fluid–structure interaction. The research examined the settling of rocks during rockfall, along with the forces and movements associated with the deposition process. The results show that the rockfall pipeline experienced vortex-induced vibrations (VIVs) caused by ocean currents during operation. The maximum settling velocity of the rocks throughout the rockfall process reached 2.2 m/s, with a final stable velocity of 1.5 m/s. These simulation results offer critical insights for improving the design and functionality of the rockfall pipeline, thereby enhancing the protection of underwater infrastructure.

Submarine cables are widely laid all over the world. However, they are not completely fixed in practice and are subject to displacement by currents and typhoons. To maintain and repair the submarine cables, it is necessary to detect their positions. Using a remotely operated vehicle (ROV) equipped with magnetometers is a common way for submarine detection. However, as ROVs develop toward electrification and large scale, the interference of electric drives on the magnetometer is significant. Magnetic interference and noise in the environment affect the signals of magnetometers, reducing the accuracy of submarine cable detection. In this paper, a two-step method is proposed to reduce the influence of magnetic noise and interference. In the first step, we eliminate magnetic interference based on its correlation with motor speed. In the second step, wavelet transform is used to eliminate environmental magnetic noise. According to the simulation and on-site test, this method can reduce the magnetic interference caused by brushless DC motors and improve the accuracy of magnetic detection and positioning of submarine cables.