Remotely Operated Underwater Vehicle Research Articles

Siliceous microfossil assemblages in the southern Emperor Seamount Chain sediments and their biogeographical and paleoceanographical implications

The taxonomic composition and abundance of siliceous microfossils in sediments is a valuable source of information about environmental changes at the sea surface today and in the geological past. This paper presents the results of a study of siliceous microplankton (radiolaria, diatoms, and silicoflagellates) in the surface calcareous sediments (silty foraminiferal oozes and sands) of the Nintoku, Jingu, Ojin, Koko, and Yuryaku guyots at the southern end of the Emperor Seamount Chain (ESC). Bottom sediments were collected using an underwater remote-operated vehicle (ROV) Comanche-18. The study revealed the taxonomic diversity and relatively high abundance of siliceous microplankton. Radiolarians are represented by 237 taxa (104 taxa from 68 genera of Spumellaria, 120 taxa from 61 genera of Nassellaria, and 13 taxa from 7 genera of Collodaria). Diatoms are represented by 60 species from 29 genera, and silicoflagellates by 5 species from 3 genera. Differences in siliceous microplankton reflect the northern boundary of warm water in the ESC, passing at approximately 38°N, between the Jingu and Ojin guyots, which coincides with the boundary of the Kuroshio Bifurcation Current, confirmed by the corals and the bathyal fauna of brittle stars (Ophiura). The absence of remains of siliceous microplankton in some sediments is probably due to dissolution, and the presence of extinct taxa from older sedimentary rocks and neritic species is due to process of reworking caused by active hydrodynamics on ESC guyots and transport by currents.

The Development of Remotely Operated Underwater Vehicle for Plastic Waste Detection with Raspberry Pi

Abstract Underwater Plastic waste has had a serious impact on the environment. Unfortunately, Detecting and collecting underwater plastic waste is still a challenge, especially in Indonesia because of its position in the water, and the water turbidity. In previous research, a computer algorithm for detecting underwater plastic waste has been developed with Yolov3. To improve the research, we developed a Remotely Operated Underwater Vehicle (ROUV) with Raspberry Pi through the Research and Development (R&D) method. This ROUV is like a submarine that operates in the water and is integrated with a camera and computer algorithm to detect plastic waste. To get close to the real condition, we created an artificial water environment in a pond with various turbidity (from 20 to 200 Nephelometric Turbidity Unit). We use 30 pieces of plastic waste in several colors: white, red, black, and transparent. The plastic waste dipped in the water and was then detected by the ROUV camera. The result shows that the effective threshold for object detection is around 100 Nephelometric Turbidity Unit (NTU). Below 100 NTU, although the number of detected plastic images decreases as the turbidity increases, the visibility and contrast still allow for reasonably good object detection. The average confidence value for detection at turbidity levels below 100 NTU is 77%. At high turbidity conditions, the detection model may require adjustment or retraining with data that reflects those turbidity conditions.

Lidar-Based Obstacle Detection and Path Prediction for Unmanned Surface Vehicles

Abstract Unmanned Surface Vehicles (USVs) represent an advanced technology with a wide range of applications in maritime contexts, and they offer a promising alternative to manned systems, particularly for the provision of services such as riverbed mapping. Furthermore, the use of USVs in combination with other robotic systems, such as flying drones, remotely operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs), opens up innovative ways to inspect and monitor maritime infrastructure. However, the use of these systems in dynamic environments, such as ports or shipping lanes, requires a high degree of adaptability and precision in navigation to manoeuvre safely between other traffic participants and obstacles to prevent collisions. To address this problem, USVs require sophisticated perception systems for the precise detection and classification of nearby objects. Leveraging Light Detection and Ranging (LiDAR) technology, which is renowned for its efficacy in obstacle avoidance in robotics, this paper outlines the adaptation of a LiDAR sensor for USVs. The proposed pipeline enables the detection of other moving vessels and the accurate determination of their positions and trajectories up to 150 m from the USV. This paper introduces an obstacle detection system and validates it within a port setting. A methodical approach to LiDAR data preprocessing, clustering, and point cloud extraction will be outlined. Furthermore, it explores the application of an Unscented Kalman Filter (UKF) for the projection of motion paths of identified entities. This advanced form of data analysis provides the ability to predict the future position and path of potential obstacles, optimize decision-making for autonomous navigation algorithms and significantly improve the safety of USV operations. The pipeline is tested experimentally in sea trials by enacting five different scenarios that USV may encounter in a port setting. The results of the pipeline’s tracking capabilities are compared to the ground truth data collected by the tracked vessel and plotted to visualize the error.

Using sea lion-borne video to map diverse benthic habitats in southern Australia

Across the world’s oceans, our knowledge of the habitats on the seabed is limited. Increasingly, video/imagery data from remotely operated underwater vehicles (ROVs) and towed and drop cameras, deployed from vessels, are providing critical new information to map unexplored benthic (seabed) habitats. However, these vessel-based surveys involve considerable time and personnel, are costly, require favorable weather conditions, and are difficult to conduct in remote, offshore, and deep marine habitats, which makes mapping and surveying large areas of the benthos challenging. In this study, we present a novel and efficient method for mapping diverse benthic habitats on the continental shelf, using animal-borne video and movement data from a benthic predator, the Australian sea lion (Neophoca cinerea). Six benthic habitats (between 5-110m depth) were identified from data collected by eight Australian sea lions from two colonies in South Australia. These habitats were macroalgae reef, macroalgae meadow, bare sand, sponge/sand, invertebrate reef and invertebrate boulder habitats. Percent cover of benthic habitats differed on the foraging paths of sea lions from both colonies. The distributions of these benthic habitats were combined with oceanographic data to build Random Forest models for predicting benthic habitats on the continental shelf. Random forest models performed well (validated models had a >98% accuracy), predicting large areas of macroalgae reef, bare sand, sponge/sand and invertebrate reef habitats on the continental shelf in southern Australia. Modelling of benthic habitats from animal-borne video data provides an effective approach for mapping extensive areas of the continental shelf. These data provide valuable new information on the seabed and complement traditional methods of mapping and surveying benthic habitats. Better understanding and preserving these habitats is crucial, amid increasing human impacts on benthic environments around the world.

Underwater temperature and pressure monitoring for deep-sea SCUBA divers using optical techniques

The safety of SCUBA divers remains at high risk in deep-sea owing to multiple factors such as dangerous surrounding, rely upon technical equipment necessary for life support, decreased underwater navigation, and communication infrastructure. Gradual decrease and increase in water temperature and pressure corresponding to depth are among the most common problems that cause most of the fatalities in deep-sea diving. Therefore, different gadgets for accurate measurement of vital parameters, reliable navigation, and seamless communication are of prime importance. In this paper, we propose an all-optical technique for local and remote monitoring of underwater temperature and pressure for deep-sea SCUBA divers based on fiber Bragg grating (FBG) sensors and underwater optical communication-single mode fiber (UWOC-SMF) integrated transmission system. The proposed technique is implemented using two FBG temperature and pressure sensors fixed over diver’s suit and UWOC-SMF integrated transmission system for simultaneous local and remote monitoring of underwater temperature and pressure. Remote monitoring of underwater temperature and pressure is achieved at ship station through a remotely operated underwater vehicle (ROV) and UWOC-SMF integrated transmission system by means of shifts in the original Bragg wavelengths of sensors due to temperature and pressure variations. The performance of the sensors is analyzed for pressure and temperature in the range of 0 to 6.4 MPa (≈0 to 655 mH2O) and 40 to −2°C, respectively corresponding to different depths. The results show that the proposed technique can work well in the deep ocean over a range of pressures and temperatures of 0–7 MPa and 40 to −2°C while achieving a temperature sensitivity of 4.3 p.m./°C and a pressure sensitivity of 30.5 p.m./MPa. Clear spectra of reflected signals from FBG sensors at ship station are achieved after signal transmission over UWOC-SMF hybrid link.

Detection of Flaws in Ship Hull Using Underwater Remotely Operated Vehicle

Detection of Flaws in Ship Hull Using Underwater Remotely Operated Vehicle

Underwater Remotely Operated Vehicle Control System Ar-chitecture

Underwater Remotely Operated Vehicle Control System Ar-chitecture

Launch and recovery of a work class ROV through wave zone in small offshore service vessel

The deployment of remotely operated underwater vehicle (ROV) from a small offshore service vessel (OSV) based on single point mooring system (SPMS) method is recently adopted in offshore renewable energy sector. However, the tension spike in wire, also known as snap load, often occurs when the ROV passes through the wave zone in launching and lifting operation of deployment. In this study, a practical numerical model for predicting wire tension during launch and recovery of ROV is developed and validated by wave flume test of a 1:10 scaled model. The numerical simulations reveal that the ROV deployment at vessel stern along with an appropriate reduction of horizontal distance from the hull are reliable safety strategies for reducing wire tension. By adopting the new deployment strategy, the annual operational capacity can be expanded by approximately 6% when the safe operational limit of ROV under a significant wave height of 1.25 m. Based on the comprehensive numerical simulation, the newly developed safe operating envelope provides a further guidance for onboard ROV operation in the O&M of offshore wind farms.

Design of Remotely Operated Underwater Vehicle (ROUV) for Underwater Metal Detection

Design of Remotely Operated Underwater Vehicle (ROUV) for Underwater Metal Detection

Integration of Multiple Sensors into an ROV for Remote Measurement in the Fukushima Daiichi Nuclear Power Station

To measure and analyze the distribution and criticality of submerged fuel debris “in situ” in the decommissioning process of the Fukushima Daiichi Nuclear Power Station (1F), we developed a system for remote measurement using multiple sensors consisting of the neutron sensor, the sonar, and the sub-bottom profiler (SBP) mounted on a small remotely operated underwater vehicle (ROV). First, the locations presumed to contain fuel debris were explored based on the information of the water bottom shape obtained using the sonar and the bottom surface substructure obtained using the SBP. Second, the system identified the location of fuel debris by detecting neutrons emitted by spontaneous fissions of fuel debris using the neutron sensor with diamond elements. Simulated fuel debris was placed at the bottom of a test water tank that simulated the pedestal. In the primary containment vessel (PCV) of 1F, and a verification test of remote measurement was conducted using the ROV mounted on the multiple sensors. The desired results were obtained.

Investigation of 3D Printed Underwater Thruster Propellers Using CFD and Structural Simulations

Unmanned Surface Vehicles (USV) and Autonomous or Remotely Operated Underwater vehicles (AUV, ROV) are developing and spreading rapidly in various industries. A common feature of these vehicles is that they are propelled by small plastic (or metal) propellers in most cases. Additive manufacturing can offer an excellent opportunity for rapid prototyping and the development of new models. This paper aims to investigate the fundamental aspects to be considered in the geometric design and manufacturing of small (diameter less than 100 mm) PLA (Polylactic acid) propellers 3D-printed using Fused Filament Fabrication (FFF) technology. In-service deformation of 3D-printed PLA ducted propellers with average geometry was investigated to determine the effect on the thrust and torque on the blades. For this purpose, one-directional FSI (Fluid Solid Interaction) simulations were performed using CFD (Computational Fluid Dynamics) and structural simulations. The propeller CAD geometries were generated using an in-house MATLAB script. The variable parameters of each version are the thickness, skew, and rake of the propeller blades. For the structural simulations, it was considered that the material properties of PLA parts printed with FFF technology depend on the print orientation. The results of the simulations show that except for extreme geometries (e.g., thin blades, skew, or rake more than 10°), the deformation of small PLA ducted propellers is not significant. CFD studies of the deformed geometries have shown that the resulting deformation has no significant effect on the thrust and torque of the propeller and thruster.

Hybrid Cable Thruster Actuated Remotely Operated Underwater Vehicle

This paper introduces a novel Hybrid Cable Thruster Actuated Remotely Operated Underwater Vehicle (HCT-ROV), merging the strengths of ROVs and Cable-Driven Parallel Robots for enhanced underwater capabilities. It presents the world's first HCT-ROV prototype, together with a control law using Quadratic Programming (QP) for efficient operation. Extensive MATLAB simulations and prototype tests demonstrate superior performance in tasks like object transportation. This research work paves the way for advanced underwater exploration and operations, emphasizing the need for further optimization in real-world applications.

ROV6D: 6D Pose Estimation Benchmark Dataset for Underwater Remotely Operated Vehicles

ROV6D: 6D Pose Estimation Benchmark Dataset for Underwater Remotely Operated Vehicles

A Control Architecture for Developing Reactive Hybrid Remotely Operated Underwater Vehicles

This article introduces a control architecture designed for the development of Hybrid Remotely Operated Underwater Vehicles. The term ”Hybrid” characterizes Remotely Operated systems capable of autonomously executing specific operations. The presented architecture maintains teleoperation capabilities while enabling two fully autonomous applications. The approach emphasizes the implementation of reactive navigation by exclusively utilizing data from a Mechanical Scanned Imaging Sonar for control decisions. This mandates the control system to solely react to data derived from the vehicle’s environment, without considering other positioning information or state estimation. The study involves transforming a small-scale commercial Remotely Operated Underwater Vehicle into a hybrid system without structural modifications, and details the development of an intermediate Operational Control Layer responsible for sensor data processing and task execution control. Two practical applications, inspired by tasks common in natural or open-water aquaculture farms, are explored: one for conducting transects, facilitating monitoring and maintenance operations, and another for navigating toward an object for inspection purposes. Experimental results validate the feasibility and effectiveness of the authors’ hypotheses. This approach expands the potential applications of underwater vehicles and facilitates the development of Hybrid Remotely Operated Underwater Vehicles, enabling the execution of autonomous reactive tasks.

Numerical Investigation on Hydrodynamic Characteristics and Drag Influence of an Open-Frame Remotely Operated Underwater Vehicle

Remotely operated underwater vehicles (ROVs) have been widely used in deep-sea resource exploitation and industrial engineering operations. To perform these tasks accurately in the deep-sea environment, stable motion control has become a key area of research on ROV systems, which has led to the importance of analyzing the hydrodynamic characteristic of ROVs. But a systematic methodology for analyzing the hydrodynamic characteristics of ROVs is still lacking nowadays. In this paper, systematic numerical simulation methods for analyzing hydrodynamic characteristics and shape optimization of a work-class ROV are conducted, and details of simulation procedures based on computational fluid dynamics are studied, which can be a foundation for robust controller design.

DEVELOPMENT OF UNDERWATER ROV (REMOTELY OPERATED VEHICLE) SYSTEMS AND MECHANISM

Remotely Operated Vehicle or abbreviated as ROV is an underwater explorer robot where the robot is controlled remotely by an operator using a remote control system. Water ecosystems certainly have various kinds of hazards that cause harm to divers, such as wild animals, waters contaminated with toxic waste, limited oxygen, and many other risks. Based on these problems, research was carried out, namely the Design and Development of Underwater ROV (Remotely Operated Vehicle) Mechanisms and Systems where the tool built is an underwater robot that uses 8 DC motors to be able to perform 12 types of movements under water. The final result obtained by the ROV is that it is able to perform all of these movements except for the right somersault and left somersault. The speed and direction of rotation of the motor is controlled by a device, namely the BTS7960 motor driver. This robot aims to measure pressure and temperature and capture images underwater to a depth of 4m. Pressure and temperature measurements were made using a BMP180 pressure sensor and a DS18B20 temperature sensor where the measurement results will be displayed on a 16x2 LCD. Based on the test results, the pressure sensor has an error rate of 3.6% and a temperature sensor of 0.34%. Images and videos are captured by a device, namely a CCTV camera where the device is connected to a laptop device as a monitor. The test produced results in the form of images and videos that were quite clear.

Utility of remotely operated underwater vehicle in flood inundation mapping for dam failure: A case study of Lake Tuscaloosa Dam

AbstractA remotely operated underwater vehicle (ROV) is a tethered underwater mobile device that can conduct a bathymetric survey cost‐efficiently. Assessment of the utility of ROV‐based bathymetric surveys in flood inundation mapping remains limited. This study aims to examine the utility of ROV‐based bathymetric surveys in high‐resolution flood inundation mapping for a hypothetical case study of the Lake Tuscaloosa Dam breach in the state of Alabama, USA. This study conducted the sensitivity test of flood inundation mapping to the river channel depth (ROV‐based vs. digital elevation model [DEM]‐based) and initial flow condition (e.g., wet vs. dry), via six different simulations of the parallelized diffusion hydrodynamic model (pDHM). This study found that the ROV‐based pDHM runs had higher maximum water depths over the flood‐inundated areas, ranging from +73% to +166% of the simulated depths of the DEM‐based pDHM runs. However, the impact of initial streamflow condition on the maximum depths was limited. This study also found that the pDHM runs with a dry initial flow condition delayed the time to reach the maximum depth after the dam breach by 2 h relative to the pDHM runs with a wet initial streamflow condition. This study suggests that ROV‐based bathymetry surveys improve flood inundation mapping by emphasizing the influence of river channel depth, initial streamflow conditions, and bathymetry, thereby bolstering community resilience to a potential human‐made hazard such as dam failure.

Unmotorize ROV gripper to catch profiling floats

This paper proposes an ROV (Remotely Operated underwater Vehicle) gripper for retrieving cylindrical profiling floats. In order to fit several types of ROVs and to be easily installed, the gripper is not motorized, using only the robot’s movements to catch the floats by simply moving forward on them. Then, the gripper uses the turnstile and freewheel concept to grasp and hold the float, with a safety release system to free an unwanted catch. The effectiveness of the clamp was tested in the pool and in the lake, with two actual rescues of lost floats. The limits of the methods are discussed.

Design and Fabrication of a Low-Cost Multi-Purpose Underwater Remotely Operated Vehicle

Remotely Operated Underwater Vehicles (ROVs) are emerging potential technology for ocean research, environmental and geochemical studies, mine hunting, surveillance, and commercial usage. Due to their affordability, simplicity in handling and deployment, appropriateness for deep-sea diving, increased mobility, and ability to operate in harsh settings, underwater vehicles—both autonomous and remotely controlled—have grown in popularity. The goal is to develop and test a remotely operated underwater vehicle (ROV) that is lightweight, affordable, and capable of conducting surveys in shallow waters. The design, production, and experimental findings of such an ROV are the focus of this paper. The mechanical design, thruster characteristics, electrical systems, and software architecture of the graphical user interface (GUI) for the proposed vehicle are all thoroughly explained. In contrast to autonomous underwater vehicles, the planned ROV is totally controlled from the base station using a live camera feed and other sensors (AUV). In contrast to the majority of AUVs, it provides real-time results from its various sensors and takes human commands via two-way communication. Comprehensively addressed, the results and answers are provided. Constraints on the mechanical design’s weight and portability, electronics’ power requirements, and the length of the umbilical cord are all addressed. It is also explored how to strengthen the paradigm and make it a for-profit enterprise with more improvements.

Design and Implementation of a Six-Degrees-of-Freedom Underwater Remotely Operated Vehicle

In recent decades, there has been considerable interest in developing underwater remotely operated vehicles (ROVs) due to their vital role in exploring ocean depths to perform missions in various applications, including offshore oil and gas, military and defense, scientific research, and aquaculture. To this end, researchers must consider multiple aspects to develop ROVs, such as general design, power and thrust system, navigation and control, and obstacle avoidance. Accordingly, this paper proposes an integrated framework for designing and implementing an ROV prototype, considering the mechanical, electrical, and software systems. Eventually, image processing was implemented using Python to examine the ROV’s capabilities in performing underwater missions. The proposed design employs six thrusters to provide controllability of the ROV in six-degrees-of-freedom (DOF). We coated the track width of the printed circuit board (PCB) with a composite mixture of tin, silver, and gold to resist corrosion and harsh environments, enhance the circuit performance and solderability, and increase its life span. The PCB was designed to sustain 30 A with 10 cm × 10 cm dimensions. The image processing results revealed that the proposed ROV could successfully identify the benthic species, follow the desired routes, detect cracks, and analyze obstacles.