In this paper, in order to overcome certain limitations of previously commercialized platforms, a new integrated unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV) platform connected via underwater cable capable of acquiring real-time underwater data and long-time operation are studied. A catamaran-type USV was designed to overcome the limitations of an ocean environment and to play the role as the hub of power supply and communication for the integrated platform. Meanwhile, the UUV was designed as torpedo-shaped to minimize hydrodynamic resistance and its hardware design was focused on processing and sending the underwater camera and sonar data. The underwater cable driven by a winch system was installed to supply power from the USV to the UUV and to transmit acquired data form underwater sonar sensor or camera. Different from other previously studied cooperation system of USVs and autonomous underwater vehicles (AUVs), the merit of the proposed system is real-time motion coordination control between the USV and UUV while transmitting large amount of data using the tether cable. The main focus of the study is coordination of the UUV with respect to the global positioning system (GPS) attached at USV and verification of its performance throughout field tests. Waypoint tracking control algorithm was designed and implemented on USV and relative heading, distance control for USV–UUV coordination was implemented to UUV. To ensure the integrity of the coordination control of the integrated platform, a study on accurate measurement system of the relative position between the USV and the UUV by using the GPS and the ultrashort baseline (USBL) device was performed. Individual tests were conducted to verify the performance of USBL and AHRS, which provide the position and heading data of UUV among the sensors mounted on the actual platform, and the effectiveness of the obtained sensor data is presented. Using the accurate measurement system, a number of field tests were conducted to verify the performance of the integrated platform.

Among unmanned surface vehicle (USV) components, underwater thrusters are pivotal in their mission execution integrity. Yet, these thrusters directly interact with marine environments, making them perpetually susceptible to malfunctions. To diagnose thruster faults, a non-invasive and cost-effective vibration-based methodology that does not require altering existing systems is employed. However, the vibration data collected within the hull is influenced by propeller-fluid interactions, hull damping, and structural resonant frequencies, resulting in noise and unpredictability. Furthermore, to differentiate faults not only at fixed rotational speeds but also over the entire range of a thruster’s rotational speeds, traditional frequency analysis based on the Fourier transform cannot be utilized. Hence, Continuous Wavelet Transform (CWT), known for attributions encapsulating physical characteristics in both time-frequency domain nuances, was applied to address these complications and transform vibration data into a scalogram. CWT results are diagnosed using a Vision Transformer (ViT) classifier known for its global context awareness in image processing. The effectiveness of this diagnosis approach was verified through experiments using a USV designed for field experiments. Seven cases with different fault types and severity were diagnosed and yielded average accuracy of 0.9855 and 0.9908 at different vibration points, respectively.

This study focuses on faults in the thrusters of unmanned surface vehicles, which are fatal to the integrity of their missions. As for the fault conditions, the breakage of the thruster blade and the entanglement of floating objects were selected, and a data-driven method was used to diagnose the faults. In the data-driven method, it is important to select the sensitive fault feature. In this study, vibration, current consumption, rotational speed and input voltage were selected as fault features. An experiment was conducted in an engineering water tank to obtain and analyze data on fault conditions to verify the validity of the selected features. In addition, a new fault diagnosis algorithm combining principal component analysis and Shannon entropy was applied for analyzing the correlations among fault features. This algorithm reduces the dimensionality of data while preserving their structure and characteristics, and diagnoses faults by quantifying entropy values. A fault is detected by comparing the entropy value and a predetermined threshold value, and is diagnosed by analyzing the entropy value and visualized 2D or 3D principal component results. Moreover, the fault diagnosis performance of the unmanned surface vehicle’s thruster was verified by analyzing the results for each fault condition.

Net buoyancy, as the main power source for the motion of an underwater glider, is affected by the pump or bladder that the glider adopts to change its buoyancy force in water. In this study, a new underwater glider that can dive to a depth of 400 m at a cruising speed of 2 knots, which is faster than conventional underwater gliders and is less affected by sea currents, is investigated. The UG resisting 400 m pressure on the buoyancy engine and achieving 2 knots’ speed was designed and constructed. For this UG, its steady-state attitude was studied according to the variance of the buoyancy center and the center of gravity with the buoyancy engine influenced by the displacement of the movable mass block. In motion simulation of the UG, the attitude of the UG under different displacement conditions was simulated in Simulink according to the displacements of the piston and the movable mass block. To validate the simulation performance, a UG was constructed and experiments were conducted. The simulation and experimental results were compared to show the reliability of the simulation results under limited conditions.

A typical structure of an underwater glider (UG) includes a pair of fixed wings, and the hydrodynamic force driving the glider forward as descending or ascending in the water is generated primarily by the fixed wings. In this paper, a simplified glider motion model was established to analyze the dynamics in an easier way, and whose simulation results do not differ from the original one. Also, in the paper, the effects of the wing position and wing shape on the UG to the motion were studied. Since no direct analytic approach cannot be performed, the case study of the effects of six different wing positions and three wing shapes on gliding performances which are gliding speed, gliding angle and gliding path were performed through computer simulation. The simulation results revealed that when the fixed wing is located far from the buoyancy center to the tail end, more traveling range is achieved with less energy. Also, effect of the shape difference of the wings were analyzed. Shape changes did not show much difference on the travelling performance of the UG. In addition to these, the transient mode of the UG was studied. To control this, the PID controller for the position of the mass shifter and piston were applied. By application of the PID controller to the linearized dynamics equations, it was shown that the transient behavior of the UG was quickly and steadily controlled.

Real-time command and data transfer are essential for autonomous underwater vehicle (AUV) motion control in underwater missions. Due to the limitations of underwater acoustic communication, which has a low data rate, this paper introduces a new control structure using underwater wireless optical communication (UWOC) to enable effective real-time command and data transfer. In this control structure, control inputs for the AUV attitude from outside of the water are transferred to the AUV for motion control, while its orientation data and visual images from the AUV camera are sent to the control station outside the water via the UWOC system. For demonstrating the performance of control action and data monitoring, an AUV is built with a constructed UWOC system, two vertical thrusters, and two horizontal thrusters. For attitude control of the AUV, an attitude heading reference system (AHRS) and a depth sensor are installed. Bi-directional communication in the UWOC system is achieved using a return-to-zero (RZ) modulation scheme for faster, longer-range data transfer. A signal processor converts sensor data received from the transmitted data. Finally, the hovering control performance of the AUV equipped with the UWOC system was experimentally evaluated in a water tank, achieving average root mean square errors (RMSEs) of 4.82° in roll, 2.49° in pitch, and 1.99 mm in depth, while simultaneously transmitting real-time motion data at 21.2 FPS with VGA-resolution images (640 × 480 pixels) at a communication rate of 1 Mbps.