Remotely Operated Underwater Vehicle Research Articles

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.

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.

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.

Structural design evaluation for Underwater Remotely Operated Vehicle (ROV), case study: Madura Straits

Using Remotely Operated Vehicles (ROV) is very important, especially in underwater investigations. The Madura Strait, located between the Java islands and Madura, is used as an industrial area, especially for oil and gas sources. Therefore, the ROV structure must be designed in such a way that it can withstand the hydrostatic loads it receives during operations in the deep sea. The study was conducted to determine the ROV’s ability to withstand hydrostatic loads using materials such as steel, aluminium, and HDPE. The pre-designed ROV is converted and modeled in 3D. The model formed and detailed as the basic form of the ROV is imported to the Finite Element Analysis tools to obtain the value of the stress and deformation of the ROV. Therefore, the load is adjusted to the hydrostatic pressure, with the seawater depth up to 200 m. The study structural design evaluation is able used as a reference for selecting materials used in the ROV.

Mapping of marine litter on the seafloor using WASSP S3 multibeam echo sounder and Chasing M2 ROV

Marine litter is a growing threat to the marine environment. Mapping of marine litter is becoming increasingly important to detect its potential hotspots and prevent their spread. In this paper, the applicability of the multibeam echo sounder (MBES) WASSP S3 and remotely operated underwater vehicle (ROV) Chasing M2 was tested in the detection and mapping of marine litter on the seafloor within the wider area of the St. Ante Channel (Šibenik, Croatia). Also, the precision assessment of WASSP S3 was tested at different cruising speeds. Results have shown that Chasing M2 can be used effectively for the initial detection of marine debris in shallow waters. However, if the underwater navigation and positioning system and auxiliary measurement scales are not used, the ROV has limited capabilities in deriving morphometric parameters of marine litter on the seafloor. This was determined by comparing the 3D model of a tire which was derived using video photogrammetry captured with ROV and the 3D model of a tire which was produced using a hand-held 3D scanner. Furthermore, the results have shown the WASSP S3 is not suitable for identifying marine litter smaller than 1 m at depths up to 10 m. The MBES WASSP S3 can detect marine litter that has a minimum area of 100 * 100 cm and a height of around 40 cm at depths up to 10 m. The results pointed to the need for caution when choosing an adequate sensor to detect and map marine litter on the seafloor. In addition, MBES interval measurements have shown that WASSP S3 precision is in the centimeter range (<10 cm) at different cruising speeds. The obtained results have helped to establish the guidelines for the integrated use of MBES, ROV, and UAV in the detection of marine litter on the seafloor.

An Ultracompact Underwater Pulsed Digital Holographic Camera With Rapid Particle Image Extraction Suite

This article presents the design, development, and testing of an ultracompact underwater pulsed digital holographic camera (named weeHoloCam) that has been successfully deployed in the North Sea. With a footprint of 9 cm diameter × 60 cm long and weighing just 3.5 kg, to our knowledge, this is the lightest and most compact system of its kind in the world. It can be easily adapted for mounting on remotely operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs). weeHoloCam can record 12 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> of the water column per hologram at 20 Hz and has a capacity to continuously record up to 200 000 holograms, each 5 MB in size. Along with the holographic camera, a field-programmable gate array (FPGA)-accelerated hologram analysis suite has been developed. The 838 megapixel/s reconstruction speed demonstrated is the highest reported speed for a single FPGA implementation to date. This is an extremely important development as rapid processing of recorded holograms is vital for the viability of subsea holographic cameras. weeHoloCam was successfully trialed in the North Sea, recording close to a hundred thousand holograms and extracting particle images within those holograms at a rate of 190 per min. weeHoloCam has the potential to play an important role in several oceanic studies: spatial and temporal monitoring of plankton species; study of plankton dynamics; study of vertical transport of floc; and monitoring microplastic pollution in the ocean, to name but a few.

Robust automatic net damage detection and tracking on real aquaculture environment using computer vision

Sea cage inspection is a crucial task in marine aquaculture for both controlling the quality in the fish development process and the environmental impact of these facilities. Net damage in sea cages can cause fish to escape from fish farms to the open sea, producing serious economic losses and compromising the surrounding marine ecosystem. Currently, the most sophisticated inspection processes used in the industry rely on human visual inspection of underwater videos captured with tele-operated underwater ROV (Remotely Operated Vehicles). This process is tedious, time consuming, imprecise, highly dependant on the operator level of expertise, and has low verifiability.This article presents a comprehensive algorithm for automatic net damage detection in sea cages for aquaculture oriented to on-ROV processing and real-time processing. The proposed approach takes a video stream from an on-ROV camera, segments the image frames to separate the net of the sea cage from the background, and applies noise reduction tuned for underwater conditions. Then, to perform net damage detection, the mesh net hole areas are analyzed for detecting outliers that represent potential damage. Finally, holes neighboring to the outliers are analyzed to reduce perspective errors, and a spatial-temporal criterion using tracking is applied, to reduce the chance of false positives. The algorithm was first tested using a set of public images for comparison with state-of-the-art approaches and repeatability of the tests, and then using a dataset of real ROV inspection sequences to evaluate its effectiveness in real-world scenarios. Results show that our approach presents high levels of accuracy even for adverse scenarios and is adequate for real-time processing in embedded platforms.

ROUV HEADING BY A FRACTIONAL-ORDER PI CONTROLLER

To control a remotely operated underwater vehicle (ROUV) of the observation ROUVs class, the interactions among mechanical, electronic and information processing elements call for an integrated approach at all design and development stages. Different methodologies must be combined in a multi-formalism modelling approach supported by a suitable simulation and prototyping environment. The proposed approach further involves the development of a digital twin ROUV prototype in the Gazebo-based simulator to assess performance reliably, and the utilization of a ROUV controller board (stm32F407, Quad-core Cortex-A7) with a digital camera and an inertial measurement unit (3D accelerometer, 3D gyroscope, compass) to implement and run the designed control algorithms in real-time. A mathematical model of the system is derived to design a fractional-order PI controller of the ROUV heading in the horizontal plane.

Cooperative path-following control of a remotely operated underwater vehicle for human visual inspection task

In recent years, significant attention has been paid to remotely operated underwater vehicles (ROVs) in the performance of underwater tasks, such as the inspection and maintenance of the underwater infrastructure. The workload of ROV operators tends to be high, even for the skilled operators. Therefore, assistance methods for the operators are desired. This study focuses on a task in which a human operator controls an underwater robot to follow a certain path while visually inspecting objects in the vicinity of the path. In such a task, it is desirable to achieve the speed of trajectory control manually because the visual inspection is performed by a human operator. However, to allocate resources to visual inspection, it is desirable to minimize the workload on the path-following by assisting with the automatic control. Therefore, the objective of this study is to develop a cooperative path-following control method that achieves the above-mentioned task by expanding a robust path-following control law of non-holonomic wheeled vehicles. To simplify this problem, we considered a path-following and visual objects recognition task in a two-dimensional plane. We conducted an experiment with participants (n = 16) who completed the task using the proposed method and manual control. We compared results in terms of object recognition success rate, tracking error, completion time, attention distribution, and workload. The results showed that both the path-following errors and workload of the participants were significantly smaller with the proposed method than with manual control. In addition, subjective responses demonstrated that operator attention tended to be allocated to object recognition rather than robot operation tasks with the proposed method. These results demonstrate the effectiveness of the proposed cooperative path-following control method.

Autonomous Control of the Underwater Remotely Operated Vehicle in Collision Situation with Stationary Obstacle

Abstract The article considers the problem of autonomous control of the underwater remotely operated vehicle mini Remotely Operated Vehicle (ROV) in a collision situation with a stationary obstacle. The control of the collision avoidance process is presented as a synthesis of fuzzy proportional-differential controllers for the control of distance and orientation concerning the detected stationary obstacle. The control of the submergence depth of the underwater vehicle has been adopted as a separate control flow. A method to obtain the main motion parameters of the underwater vehicle relative to the detected stationary obstacle using a Laser-based Vision System (LVS) and a pressure sensor coupled to an Inertial Measurement Unit (IMU) is described and discussed. The result of computer implementation of the designed fuzzy controllers for collision avoidance is demonstrated in simulation tests and experiments carried out with the mini ROV in the test pool.

Position Tracking of an Underwater Robot Based on Floating-Downing PI Control

A remotely operated underwater vehicle (ROV) is crucial in ocean exploration and underwater missions. An ROV is manipulated through a tether cable by an operator on shore or mother boat, and it can be used for underwater observations or as a robotic arm to take samples back. The position control and movement of an ROV are not stable due to buoyancy, ocean current, and surge waves. To overcome the influence of these disturbances on the ROV, we propose a switch proportional-integral (PI) controller combined with a buck-boost converter (BBC) to process the ROV’s position following. In this paper, a six-axis ROV was designed and implemented. The ROV controller was designed by a NI-roboRIO-based embedded system, which includes a pressure sensor, an accelerometer, six thrusters, and two webcams. The LabVIEW human–machine interface was designed to integrate the control system, sensors, and thrusters. The PI controller was employed to perform the station-keeping and trajectory following. Different PI control parameters were used for the ROV floating-up and diving-down in the sine-wave trajectory following. Experimental results showed that the proposed switch PI control scheme is robust for the position tracking of the underwater robot. The contribution of this study is that we proposed a novel switch proportional-integral controller combined with a buck-boost converter and applied the controller to a natural underwater vehicle, not a mathematical model. The experiments showed that the proposed controller can resist the disturbance of the aquatic environment.

Hierarchical trajectory tracking control for ROVs subject to disturbances and parametric uncertainties

Trajectory tracking control is crucial for a remotely operated underwater vehicle (ROV), but the performance can be degraded due to disturbances, process noises, and parametric uncertainties. Therefore, a hierarchical control scheme is proposed to handle this problem. Firstly, a 4DOF kinematic model and dynamic model of the ROV are constructed. Ocean current disturbance is considered in the kinematic model and the dynamic model when tracking the reference trajectory. Parametric uncertainties are also considered on the dynamic model. Secondly, model predictive control using extended state based Kalman filter (ESKF-MPC) is used to design a kinematic controller (velocity layer) based on the kinematic model to generate virtual expected velocities. ESKF-MPC can not only solve constraints on velocities, but also estimate states and ocean current disturbance, which is beneficial for improving the robustness to ocean current disturbance. Thirdly, adaptive sliding mode control (ASMC) is applied to construct a dynamic controller (position layer) to compute optimal forces and moments based on the dynamic model and virtual expected velocities output by the kinematic controller, which is robust to parametric uncertainties and can solve the chattering problem. Finally, simulations are performed to validate the performance of the proposed hierarchical control scheme.

Mesophotic Reefs of the Largest Brazilian Coastal Protected Area: Mapping, Characterization and Biodiversity

Mesophotic reefs are poorly known worldwide despite their great ecological relevance and management importance for coral reef conservation strategies. To aid in filling this gap, we conducted a pioneering, large-scale survey, covering a total of around 315 miles in length, in the largest Brazilian coastal Marine Protected Area (MPA) Costa dos Corais. From the digital bathymetry model (30 to 50 m depth) generated by a multibeam echo sounder, we selected areas of greater geomorphological diversity for a detailed investigative expedition of mesophotic ecosystems. Various sampling techniques were used: single-beam echo sounders for detailing the relief, a remotely operated underwater vehicle (ROV) for habitat type investigation, baited remote underwater video (BRUV) for collecting images of the fish community, and scuba diving to perform transects describing the benthic and fish community. We analyzed reef environments from 20 to 68 m deep. As a result, we present the mapping and geomorphological characterization of two compartments of mesophotic reefs at 21–45 m depth and an image library of mesophotic ecosystems with the species description and indications of whether it is a new record in the region. Biodiversity data were collected covering eight species of sponges, with greater abundance for Ircinia spp., Aplysina spp., and Xestospongia muta; eight from corals, mainly Siderastrea spp. And Montastrea cavernosa; and 68 species of reef fish, with the Labridae family (including Scarinae—11 species) being the richest. Our results demonstrate the importance of mesophotic reefs for MPA Costa dos Corais reef biodiversity and, with that, the need to protect these areas through the application of local conservation strategies, such as the creation of “no-take zones”.

Simultaneous Control and Guidance of an AUV Based on Soft Actor-Critic.

The marine environment is a hostile setting for robotics. It is strongly unstructured, uncertain, and includes many external disturbances that cannot be easily predicted or modeled. In this work, we attempt to control an autonomous underwater vehicle (AUV) to perform a waypoint tracking task, using a machine learning-based controller. There has been great progress in machine learning (in many different domains) in recent years; in the subfield of deep reinforcement learning, several algorithms suitable for the continuous control of dynamical systems have been designed. We implemented the soft actor–critic (SAC) algorithm, an entropy-regularized deep reinforcement learning algorithm that allows fulfilling a learning task and encourages the exploration of the environment simultaneously. We compared a SAC-based controller with a proportional integral derivative (PID) controller on a waypoint tracking task using specific performance metrics. All tests were simulated via the UUV simulator. We applied these two controllers to the RexROV 2, a six degrees of freedom cube-shaped remotely operated underwater Vehicle (ROV) converted in an AUV. We propose several interesting contributions as a result of these tests, such as making the SAC control and guiding the AUV simultaneously, outperforming the PID controller in terms of energy saving, and reducing the amount of information needed by the SAC algorithm inputs. Moreover, our implementation of this controller allows facilitating the transfer towards real-world robots. The code corresponding to this work is available on GitHub.