Search Results (139)

Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater manipulation, and the alternative of using professional divers is ruled out due to the risk involved. This work presents and experimentally validates an autonomous, dual-I-AUV (Intervention–Autonomous Underwater Vehicle) system capable of assembling rigid pipeline segments through coordinated actions in a confined underwater workspace. The first I-AUV is a Girona 500 (4-DoF vehicle motion, pitch and roll stable) fitted with multiple payload cameras and a 6-DoF Reach Bravo 7 arm, giving the vehicle 10 total DoF. The second I-AUV is a BlueROV2 Heavy equipped with a Reach Alpha 5 arm, likewise yielding 10 DoF. The workflow comprises (i) detection and grasping of a coupler pipe section, (ii) synchronized teleoperation to an assembly start pose, and (iii) assembly using a kinematic controller that exploits the Girona 500’s full 10 DoF, while the BlueROV2 holds position and orientation to stabilize the workspace. Validation took place in a 12 m × 8 m × 5 m water tank. Results show that the paired I-AUVs can autonomously perform precision pipeline assembly in real water conditions, representing a significant step toward fully automated subsea construction and maintenance. Full article

This study presents a new intelligent aquatic farming surveillance system that tackles real-time monitoring challenges in the industry. The main technical break-throughs of this system are evident in four key aspects: First, it achieves the smooth integration of remotely operated vehicles (ROVs), sensors, and real-time data transmission. Second, it uses a mobile communication architecture with buoy relay stations for distributed edge computing. This design supports future upgrades to Beyond 5G and satellite networks for deep-sea applications. Third, it features a multi-terminal control system that supports computers, smartphones, smartwatches, and centralized hubs, effectively enabling monitoring anytime, anywhere. Fourth, it incorporates a cost-effective modular design, utilizing commercial hardware and innovative system integration solutions, making it particularly suitable for farms with limited resources. The data indicates that the system’s 4G connection is both stable and reliable, demonstrating excellent performance in terms of data transmission success rates, control command response delays, and endurance. It has successfully processed 324,800 data transmission events, thoroughly validating its reliability in real-world production environments. This system integrates advanced technologies such as the Internet of Things, mobile communications, and multi-access control, which not only significantly enhance the precision oversight capabilities of marine farming but also feature a modular design that allows for future expansion into satellite communications. Notably, the system reduces operating costs while simultaneously improving aquaculture efficiency, offering a practical and intelligent solution for small farmers in resource-limited areas. Full article

Hydrodynamic coefficients determine the behavior of all simulated underwater vehicles. Therefore, it is essential to precisely define their values when aiming to replicate a real vehicle. Generally established procedures for obtaining them tend to have limitations, especially in transient responses. To address these issues, this paper proposes a comprehensive methodology for obtaining the hydrodynamic coefficients of an underwater vehicle. The main novelty is the combination of empirical measurements as a first step and evolutionary algorithms as a final step for optimizing the coefficients. The proposed methodology is described and applied to a commercially available remotely operated vehicle (ROV) BlueROV2, followed by analyzing the results in detail and including several tests that compare it to the real vehicle to validate its adequacy. Full article

A previously buried paleosol was found on the continental shelf during a study of sea floor scour, nucleated by large artificial reef structures such as vessel hulks, barges, train cars, military vehicles, etc., called “scour nuclei”. It is a relic paleo-land surface of sapling-sized tree stumps, root systems, and fossil animal bone exhumed by scour processes active adjacent to the artificial reef structure. Over the span of five research cruises to the site in 2022–2024, soil samples were taken using hand excavation, PONAR grab samplers, split spoon, hollow tube auger, and a modified Shelby-style push box. High-definition (HD) video was taken using a Remotely Operated Vehicle (ROV) and diver-held cameras. Radiocarbon dating of wood samples returned ages of 42,015–43,417 calibrated years before present (cal yrBP). Pollen studies, together with the recovered macrobotanical remains, support our interpretation of the site as a freshwater forested wetland whose keystone tree species was Taxodium distichum—bald cypress. The paleosol was identified as an Aquult, a sub-order of Ultisols where water tables are at or near the surface year-round. A deep (0.25 m+) argillic horizon comprised the bulk of the preserved soil. Comparable Ultisols found in Georgia wetlands include Typic Paleaquult (Grady and Bayboro series) soils. Full article

Remotely operated vehicles (ROVs) face challenges in maneuvering and rapidly detecting and repairing large offshore platforms. The accurate research on the hydrodynamics of the ROV, which moves close to the wall, is of great significance for its maneuverability. This study uses computational fluid dynamics (CFDs) to analyze the hydrodynamic characteristics of an ROV when it is moving near the wall, considering factors such as structural asymmetry, speed, and distance from the wall. This study applies multiple linear regression to extract relevant hydrodynamic coefficients and develops a mathematical model that simulates the impact of these factors on ROV performance. The results indicate that the wall’s influence on hydrodynamic forces is significant. Total resistance increases as the ROV moves closer to the wall, and the effect becomes more pronounced at higher speeds. Pressure differential resistance is the dominant factor affecting ROV performance, while viscous resistance remains low and is mostly unaffected by wall proximity. These findings provide valuable insights into calculating hydrodynamic coefficients and modeling the dynamics of ROVs with complex shapes operating near the wall. Full article

This study focuses on the remotely operated underwater vehicle (ROV) and addresses key issues in existing simulation systems, such as neglecting the influence of ocean currents on the ROV’s trajectory or only simulating the impact of ocean currents instead of combining wake flow and ocean currents. Additionally, the visualization capabilities of current simulation systems still have room for improvement. This paper develops a three-dimensional path simulation system for ocean inspection robots to tackle these challenges based on MATLAB and Simulink. The system optimizes the drag matrix of the original simulation model by decomposing the sea current into three directional components in three-dimensional space and simulating the relative velocity in each direction separately; it introduces the influence of the current wake, thus more accurately realizing the trajectory simulation of the ROV under the current perturbation. Experimental results demonstrate high consistency between the optimized model’s simulation outcomes and theoretical expectations. The proposed system significantly improves trajectory evolution stability and consistency, compared to traditional models. The findings of this study indicate that the proposed optimized simulation system not only effectively verifies the applicability of control algorithms but also provides reliable data support for ROV design and optimization. Additionally, it lays a solid foundation for further developing intelligent underwater robots based on Internet of Things (IoT) technology. Full article

This paper presents a predefined-time control approach to address slow convergence and instability in the orbit control of remotely operated vehicles (ROVs). The proposed method introduces tunable predefined-time stability (PTS), allowing precise adjustment of the system’s stability time through configurable parameters, thereby enhancing controller adaptability. A control input system ensures PTS is developed, while a fuzzy logic system (FLS) is employed to estimate unstructured uncertainties and disturbances. This integration improves robustness, reduces chattering, and eliminates singularities, making the approach well suited for systems with incomplete or unknown model data. Comprehensive simulations validate the effectiveness of the proposed method, demonstrating superior performance compared to existing control strategies and highlighting its potential for advanced ROV applications. Full article

Remotely operated vehicles (ROVs) face challenges in achieving optimal trajectory tracking performance during underwater movement due to external disturbances and parameter uncertainties. To address this issue, this paper proposes a position and attitude control strategy for underwater robots based on a reinforcement learning active disturbance rejection controller. The linear active disturbance rejection controller has achieved satisfactory results in the field of underwater robot control. However, fixed-parameter controllers cannot achieve optimal control performance for the controlled object. Therefore, further exploration of the adaptive capability of control parameters based on the linear active disturbance rejection controller was conducted. The deep deterministic policy gradient (DDPG) algorithm was used to optimize the linear extended state observer (LESO). This strategy employs deep neural networks to adjust the LESO parameters online based on measured states, allowing for more accurate estimation of model uncertainties and environmental disturbances, and compensating the total disturbance into the control input online, resulting in better disturbance estimation and control performance. Simulation results show that the proposed control scheme, compared to PID and fixed parameter LADRC, as well as the double closed-loop sliding mode control method based on nonlinear observers (NESO-DSMC), significantly improves the disturbance estimation accuracy of the linear active disturbance rejection controller, leading to higher control precision and stronger robustness, thus demonstrating the effectiveness of the proposed control strategy. Full article

In order to realize the detection of marine engineering facilities, the hardware system of a new type of remotely operated vehicle (ROV) is designed independently, and the control system, including the lower computer program and the upper computer software, is developed. At the same time, in order to explore the thrust distribution of the thruster and realize the optimization of the thrust distribution under the installation position and installation angle of the designed thruster, the mathematical model of the ROV propulsion system is established. The simulation models of ROV motion control and thrust distribution are established in MATLAB R2022a and Unity 3D, respectively. Given the thrust input of the compound motion, the sequential quadratic programming (SQP) method and the direct logic method are used to compare the simulation results of thrust distribution. Finally, the underwater attitude control experiment and the application experiment of the actual scene are carried out. Combined with the simulation and experimental results, the feasibility of using the sequential quadratic programming method to optimize the thrust allocation is verified, and it is shown that the new ROV system can basically meet the expected design requirements. Full article

The remotely operated vehicle (ROV), a vital deep-sea platform, offers key advantages, including operational duration via continuous umbilical power, high task adaptability, and zero human risk. It has become indispensable for deep-sea scientific research and marine engineering. To enhance surveys of cobalt-rich crusts (CRCs) on complex seamount terrains, the 4500-m-class Haima ROV integrates advanced payloads, such as underwater positioning systems, multi-angle cameras, multi-functional manipulators, subsea shallow drilling systems, sediment samplers, and acoustic crust thickness gauges. Coordinated control between deck monitoring and subsea units enables stable multi-task execution within single dives, significantly improving operational efficiency. Survey results from Caiwei Guyot reveal the following: (1) ROV-collected data were highly reliable, with high-definition video mapping CRCs distribution across varied terrains. Captured crust-bearing rocks weighed up to 78 kg, drilled cores reached 110 cm, and acoustic thickness measurements had a 1–2 cm margin of error compared to in situ cores; (2) Video and cores analysis showed summit platforms (3–5° slopes) dominated by tabular crusts with gravel-type counterparts, summit margins (5–10° slopes) hosting gravel crusts partially covered by sediment, and steep slopes (12–15° slopes) exhibiting mixed crust types under sediment coverage. Thicker crusts clustered at summit margins (14 and 15 cm, respectively) compared to thinner crusts on platforms and slopes (10 and 7 cm, respectively). The Haima ROV successfully investigated CRC resources in complex terrains, laying the groundwork for seamount crust resource evaluations. Future advancements will focus on high-precision navigation and control, high-resolution crust thickness measurement, optical imaging optimization, and AI-enhanced image recognition. Full article

This study proposes a control method for Remotely Operated Vehicles (ROVs) to actively dock with AUVs, to address the limitations of traditional docking and recovery schemes for Autonomous Underwater Vehicles (AUVs), such as restricted maneuverability and external disturbances. Firstly, a process and control strategy for ROV active docking with AUVs is designed, improving docking safety. Secondly, a Nonlinear Model Predictive Controller (NMPC) based on a Gaussian Function Sliding Mode Observer (GFSMO) compensation is designed for the ROV, generating smooth control inputs to achieve high-precision trajectory tracking and real-time docking. Finally, a joint simulation experiment is established through WEBOTS 2023a and MATLAB 2023a, verifying the superiority and feasibility of the designed controller and the proposed method. After parameter optimization, the simulation results show the method proposed in this study has a 90% success rate in 10 docking experiments under different disturbances. Full article

Marine life exploration is constrained by factors such as limited scuba diving time, depth restrictions for divers, costly expeditions, safety risks to divers’ health, and minimizing harm to marine ecosystems, where traditional diving often risks disturbing marine life. This paper introduces Nu (named after an ancient Egyptian deity), a 3D-printed Remotely Operated Underwater Vehicle (ROUV) designed in an attempt to address these challenges. Nu employs Long Range (LoRa), a low-power and long-range communication technology, enabling wireless operation via a manual controller. The vehicle features an onboard live-feed camera with a separate communication system that transmits video to an external real-time machine learning (ML) pipeline for fish species classification, reducing human error by taxonomists. It uses Brushless Direct Current (BLDC) motors for long-distance movement and water pump motors for precise navigation, minimizing disturbance, and reducing damage to surrounding species. Nu’s functionality was evaluated in a controlled 2.5-m-deep body of water, focusing on connectivity, maneuverability, and fish identification accuracy. The fish detection algorithm achieved an average precision of 60% in identifying fish presence, while the classification model achieved 97% precision in assigning species labels, with unknown species flagged correctly. The testing of Nu in a controlled environment has met the system design expectations. Full article

Sand waves are large-scale bed forms commonly occurring on the continental shelf seabed and can result in free spans of submarine pipelines, which may have an influence on the stability of the pipelines. Existing span rectification procedures have primarily focused on local rectification methods for free spans caused by local scour or individual spans resulting from seabed unevenness. This paper aims to present a span rectification design applicable to the pipeline crossing sand wave region, and to offer practical guidance on sand wave intervention strategies. A large-scale approach is necessary for the rectification of multiple spans across the field, which may involve the use of either a mass flow excavator (MFE) or a remotely operated vehicle (ROV) jetting tool. A comparative analysis of the estimated durations for post-lay trenching using the MFE and ROV jetting tools is also provided. In instances where the large-scale method fails to achieve span lengths suitable for long-term operation, a localized approach is necessary to address individual spans. The desired trench depth can be attained through a combination of pre-lay and/or post-lay trenching techniques. The analysis of on-bottom roughness and free span has demonstrated that, given the natural seabed profile without trenching, there are no spans surpassing the ultimate limit state (ULS) or fatigue limit state (FLS) criteria for the temporary installation scenario. Consequently, pre-lay rectification is not necessary. However, the analysis indicates that post-lay rectification is essential to meet ULS and FLS criteria under operating conditions. All spans that exceed the ULS and FLS criteria can be effectively rectified by trenching to a depth of 1 m. Full article

Efficient cleaning is crucial in aquaculture vessels; however, Remotely Operated Vehicles (ROVs) encounter difficulties in regard to trajectory tracking within confined chambers, because of structural nonlinearities and environmental disturbances. To address these challenges, this paper proposes a multi-scale dynamic sliding mode adaptive control (MDSMAC) scheme to compensate for the effects of structural nonlinearities and external disturbances, achieving precise trajectory tracking. Based on a six-degree-of-freedom motion model, an adaptive multi-scale sliding mode control mechanism is designed, enabling the system to adapt to scale variations and environmental disturbances, enhancing control accuracy and robustness. The asymptotic stability of the system is rigorously proven using the second Lyapunov method. The numerical simulation results show that the proposed method exhibits superior robustness to external disturbances and high precision in complex environments, confirming its long-term stability. Water tank experiments were conducted to further evaluate the trajectory tracking performance of the method under nonlinear system control. The results show the high level of feasibility and strong potential of the approach for practical applications. Full article

This study investigates underwater debris in a freshwater lake using remotely operated vehicles (ROVs) during two distinct survey periods: 2019 and 2024. The primary objective was to count and document visible debris (metal and plastic) on the lakebed based on ROV video recordings. A total of 356 debris items were observed in 2019, while only 39 items were recorded in 2024. The notable decrease in debris visibility in 2024 is likely attributed to dense algal growth during the survey months, which hindered the visual identification of objects on the lakebed. The study highlights the challenges of monitoring underwater debris in freshwater systems, particularly during periods of high algal activity, which can significantly impact visibility and detection efforts. While ROVs have proven effective in identifying submerged debris in clear water, this research underscores their limitations under reduced visibility conditions caused by algal blooms, turbidity diminishing the video quality. The results provide valuable insights into the temporal variation in debris visibility and contribute to ongoing efforts to improve freshwater debris monitoring techniques. Full article