Advances in Underwater Robots for Intervention

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 18759

Special Issue Editors


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Guest Editor
National Key Laboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin, China
Interests: underwater robot; remotely operated vehicle. underwater manipulation; vision based manipulation; underwater inspection; autonomous underwater vehicle

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Guest Editor
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China
Interests: unmanned underwater vehicle; electric underwater manipulator; motion tracking control; collaborative motion planning; autonomous operation

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Guest Editor
IRS-Lab, Computer Science and Engineering Department, Jaume I University, Avd. Sos Baynat s/n, 12071 Castellón de la Plana, Spain
Interests: visually guided grasping; multisensory based underwater manipulation; underwater intervention systems; telerobotics; human–robot interaction
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Special Issue Information

Dear Colleagues,

Nowadays, a relevant number of field operations in applications such as marine rescue, marine science, and offshore industries have been carried out through underwater robot manipulation. In such scenarios, most of the operation tasks are undertaken through remotely operated vehicle (ROV) or autonomous underwater vehicle (AUV) manipulations. Working-class ROV manipulations are useful for deep and heavy operations, while AUV manipulations can be realized without mothership intervention and thus help to reduce the mission cost. Currently, the challenges of underwater robot manipulations include complicated underwater vehicle manipulator mechanics, dynamics and hydrodynamics modeling on underwater robot manipulators, autonomous robot manipulation planning, and sensing-based manipulation control. This Special Issue is dedicated to recent advances in Underwater Robots and Manipulators. 

Prof. Dr. Hai Huang
Dr. Zhenzhong Chu
Prof. Dr. Pedro J. Sanz
Guest Editors

Manuscript Submission Information

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Keywords

  • complicated underwater vehicle manipulator mechanics
  • dynamics and hydrodynamics modeling on underwater robot manipulator
  • autonomous robot manipulation planning
  • vehicle and manipulator coordinate control
  • robust manipulation trajectory control
  • object tracking and vision positioning
  • visual serving underwater manipulation
  • remotely underwater operated manipulation

Published Papers (11 papers)

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Research

25 pages, 3811 KiB  
Article
Automated Deployment of an Underwater Tether Equipped with a Compliant Buoy–Ballast System for Remotely Operated Vehicle Intervention
by Ornella Tortorici, Charly Péraud, Cédric Anthierens and Vincent Hugel
J. Mar. Sci. Eng. 2024, 12(2), 279; https://doi.org/10.3390/jmse12020279 - 3 Feb 2024
Cited by 1 | Viewed by 1238
Abstract
Underwater remotely operated vehicles (ROVs) are linked to the surface through a tether that is usually controlled by a human operator. The length of the tether being deployed in the water in real time is a critical determinant of the success of the [...] Read more.
Underwater remotely operated vehicles (ROVs) are linked to the surface through a tether that is usually controlled by a human operator. The length of the tether being deployed in the water in real time is a critical determinant of the success of the mission, and the problems of entanglement and cable stretching must be anticipated to the greatest possible extent. This paper describes a low-cost and setup-friendly solution for managing the length of a neutrally buoyant tether using a balanced buoy–ballast system implemented on the part of the tether proximal to the ROV. Embedded in the system is a curvature sensor that helps to control the cable feeder on the surface. This represents a useful solution for smoothing tether movements and to damp external disturbances. The results of experiments carried out in water tanks demonstrate the benefits of this solution in allowing the cable to maintain a semi-stretched shape while ensuring that the ROV avoids being pulled by the cable. Possible applications for a surface vehicle linked to an ROV through a tether equipped with this compliant buoy–ballast system include exploration or cartography missions in shallow waters. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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25 pages, 8583 KiB  
Article
Inspection Operations and Hole Detection in Fish Net Cages through a Hybrid Underwater Intervention System Using Deep Learning Techniques
by Salvador López-Barajas, Pedro J. Sanz, Raúl Marín-Prades, Alfonso Gómez-Espinosa, Josué González-García and Juan Echagüe
J. Mar. Sci. Eng. 2024, 12(1), 80; https://doi.org/10.3390/jmse12010080 - 29 Dec 2023
Cited by 1 | Viewed by 1862
Abstract
Net inspection in fish-farm cages is a daily task for divers. This task represents a high cost for fish farms and is a high-risk activity for human operators. The total inspection surface can be more than 1500 m2, which means that [...] Read more.
Net inspection in fish-farm cages is a daily task for divers. This task represents a high cost for fish farms and is a high-risk activity for human operators. The total inspection surface can be more than 1500 m2, which means that this activity is time-consuming. Taking into account the severe restrictions for human operators in such hostile underwater conditions, this activity represents a significant area for improvement. A platform for net inspection is proposed in this work. This platform includes a surface vehicle, a ground control station, and an underwater vehicle (BlueROV2 heavy) which incorporates artificial intelligence, trajectory control procedures, and the necessary communications. In this platform, computer vision was integrated, involving a convolutional neural network trained to predict the distance between the net and the robot. Additionally, an object detection algorithm was developed to recognize holes in the net. Furthermore, a simulation environment was established to evaluate the inspection trajectory algorithms. Tests were also conducted to evaluate how underwater wireless communications perform in this underwater scenario. Experimental results about the hole detection, net distance estimation, and the inspection trajectories demonstrated robustness, usability, and viability of the proposed methodology. The experimental validation took place in the CIRTESU tank, which has dimensions of 12 × 8 × 5 m, at Universitat Jaume I. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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15 pages, 2122 KiB  
Article
A Chattering-Suppression Sliding Mode Controller for an Underwater Manipulator Using Time Delay Estimation
by Minghao Liu, Qirong Tang, Yinghao Li, Changhui Liu and Min Yu
J. Mar. Sci. Eng. 2023, 11(9), 1742; https://doi.org/10.3390/jmse11091742 - 5 Sep 2023
Viewed by 1051
Abstract
Underwater manipulators are pivotal in diverse applications, encompassing underwater pipeline repairs, salvage operations, and scientific sampling missions. However, attaining high-precision control mandates the establishment of precise mathematical models. Specifically, developing an accurate dynamic model for the underwater manipulator affixed to underwater robots proves [...] Read more.
Underwater manipulators are pivotal in diverse applications, encompassing underwater pipeline repairs, salvage operations, and scientific sampling missions. However, attaining high-precision control mandates the establishment of precise mathematical models. Specifically, developing an accurate dynamic model for the underwater manipulator affixed to underwater robots proves exceptionally demanding, primarily attributed to the uncertainties arising from water currents and the perturbations induced by the vehicle’s motion. This paper presents a novel sliding mode controller with time delay estimation for the high-precision control of an underwater manipulator mounted on an underwater vehicle. The presented controller circumvents the requirement for an exact mathematical model of the underwater manipulator, enhancing its control precision even without detailed modeling information. Moreover, the proposed controller guarantees robustness against uncertain water flow disturbances, effectively preserving the performance of the underwater manipulator under challenging underwater conditions. The proposed controller comprises two key elements. Firstly, a time delay estimator is employed to estimate the system states using feedback from intentional time-delayed control inputs and a pre-designed matrix. Additionally, a specially designed reaching law is incorporated to reduce reaching time and prevent chattering in the sliding mode control. The controller offers several advantages, including easy implementation, insensitivity to model uncertainties, and robustness in the underwater environment. Simulations and experiments demonstrate the ability of the proposed controller to effectively mitigate disturbances, eliminate chattering, and ensure precise trajectory-tracking performance. The experiments are conducted on a fully self-developed 2-degree-of-freedom (2-DOF) underwater manipulator, showcasing the superiority of the proposed controller over other alternatives. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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19 pages, 9233 KiB  
Article
A Hybrid Excitation Model Based Lightweight Siamese Network for Underwater Vehicle Object Tracking Missions
by Xiaofeng Wu, Xinyue Han, Zongyu Zhang, Han Wu, Xu Yang and Hai Huang
J. Mar. Sci. Eng. 2023, 11(6), 1127; https://doi.org/10.3390/jmse11061127 - 26 May 2023
Cited by 2 | Viewed by 1084
Abstract
Performing object tracking tasks and efficiently perceiving the underwater environment in real time for underwater vehicles is a challenging task due to the complex nature of the underwater environment. A hybrid excitation model based lightweight Siamese network is proposed to solve the mismatch [...] Read more.
Performing object tracking tasks and efficiently perceiving the underwater environment in real time for underwater vehicles is a challenging task due to the complex nature of the underwater environment. A hybrid excitation model based lightweight Siamese network is proposed to solve the mismatch between underwater objects with limited characteristics and complex deep learning models. The lightweight neural network is applied to the residual network in the Siamese network to reduce the computational complexity and cost of the model while constructing a deeper network. In addition, to deal with the changeable complex underwater environment and consider the timing of video tracking, the global excitation model (HE module) is introduced. The model adopts the excitation methods of space, channel, and motion to improve the accuracy of the algorithm. Based on the designed underwater vehicle, the underwater target tracking and target grabbing experiments are carried out, and the experimental results show that the proposed tracking algorithm has a high tracking success rate. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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16 pages, 701 KiB  
Article
Model Predictive Controller Design Based on Residual Model Trained by Gaussian Process for Robots
by Changjie Wu, Xiaolong Tang and Xiaoyan Xu
J. Mar. Sci. Eng. 2023, 11(5), 893; https://doi.org/10.3390/jmse11050893 - 22 Apr 2023
Viewed by 1374
Abstract
Model mismatch is inevitable in robot control due to the presence of unknown dynamics and unknown perturbations. Traditional model predictive control algorithms are usually based on constant value assumptions and are not able to overcome the degradation of controller performance due to model [...] Read more.
Model mismatch is inevitable in robot control due to the presence of unknown dynamics and unknown perturbations. Traditional model predictive control algorithms are usually based on constant value assumptions and are not able to overcome the degradation of controller performance due to model mismatch. In this paper, a model predictive control (MPC) algorithm based on Gaussian process regression (GPR) is proposed. Firstly, the kinematic equations of the mobile robot are established by the mechanistic analysis method; similarly, the dynamics of the mobile robot system are modeled using the second-class Lagrangian equations. Secondly, the problem of stability and reliability degradation due to model mismatch during the operation of mobile robot is considered. This paper uses a MPC algorithm with a main model plus residual model to solve the MPC closed-loop control strategy. The state at each moment is decomposed into a predicted state based on the first-principles model and a residual state. The residual state is learned by GPR in real-time and used to compensate for deviations between the real process model and the predicted model. The proposed method requires fewer data samples, enhancing the technique’s practicality. Finally, the simulation results show that the proposed algorithm is more stable and achieves the desired tracking faster. Compared with the MPC algorithm, the arrival time of the system is reduced by 28% and the speed error is controlled within 0.07. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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23 pages, 8410 KiB  
Article
Autonomous Heading Planning and Control Method of Unmanned Underwater Vehicles for Tunnel Detection
by Tianxing Xia, Dehao Cui, Zhenzhong Chu and Xing Yu
J. Mar. Sci. Eng. 2023, 11(4), 740; https://doi.org/10.3390/jmse11040740 - 29 Mar 2023
Cited by 2 | Viewed by 1403
Abstract
To address the challenge of unmanned underwater vehicle (UUV) autonomous navigation in long-distance underwater tunnel detection tasks and improve the control performance of its heading control system, a method of autonomous heading planning and control based on sonar-ranging feedback control was proposed. This [...] Read more.
To address the challenge of unmanned underwater vehicle (UUV) autonomous navigation in long-distance underwater tunnel detection tasks and improve the control performance of its heading control system, a method of autonomous heading planning and control based on sonar-ranging feedback control was proposed. This method combines UUV’s autonomous heading planning technology with the heading proportion-integral-derivative (PID) control algorithm, optimizing the acquisition method of controller input data, to impart specific adaptive characteristics to the controller. Using the ranging principle of ultrasonic spontaneous self-collection, it is possible to obtain the yaw direction and angle of the vehicle relative to the target heading in the tunnel and continuously adjust the control law to change the heading as the vehicle’s heading status changes during navigation. The effectiveness of the autonomous heading planning and control method is verified through pool experiments. The analysis and experimental results show that the proposed heading planning method achieves good control effect in UUV’s underwater tunnel detection heading control, and exhibits obvious advantages in long-distance closed tunnel environments. UUV can adaptively adjust the heading according to the tunnel environment and has a fast response and strong applicability in planning and controlling the heading. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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14 pages, 10637 KiB  
Article
Research on Underwater Image Restoration Technology Based on Multi-Domain Translation
by Teng Xue, Tianchi Zhang and Jing Zhang
J. Mar. Sci. Eng. 2023, 11(3), 674; https://doi.org/10.3390/jmse11030674 - 22 Mar 2023
Cited by 1 | Viewed by 1490
Abstract
Underwater images are crucial in various underwater applications, including marine engineering, underwater robotics, and subsea coral farming. However, obtaining paired data for these images is challenging due to factors such as light absorption and scattering, suspended particles in the water, and camera angles. [...] Read more.
Underwater images are crucial in various underwater applications, including marine engineering, underwater robotics, and subsea coral farming. However, obtaining paired data for these images is challenging due to factors such as light absorption and scattering, suspended particles in the water, and camera angles. Underwater image recovery algorithms typically use real unpaired dataset or synthetic paired dataset. However, they often encounter image quality issues and noise labeling problems that can affect algorithm performance. To address these challenges and further improve the quality of underwater image restoration, this work proposes a multi-domain translation method based on domain partitioning. Firstly, this paper proposes an improved confidence estimation algorithm, which uses the number of times a sample is correctly predicted in a continuous period as a confidence estimate. The confidence value estimates are sorted and compared with the real probability to continuously optimize the confidence estimation and improve the classification performance of the algorithm. Secondly, a U-net structure is used to construct the underwater image restoration network, which can learn the relationship between the two domains. The discriminator uses full convolution to improve the performance of the discriminator by outputting the true and false images along with the category to which the true image belongs. Finally, the improved confidence estimation algorithm is combined with the discriminator in the image restoration network to invert the labels for images with low confidence values in the clean domain as images in the degraded domain. The next step of image restoration is then performed based on the new dataset that is divided. In this way, the multi-domain conversion of underwater images is achieved, which helps in the recovery of underwater images. Experimental results show that the proposed method effectively improves the quality and quantity of the images. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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19 pages, 4988 KiB  
Article
Development and Control of an Innovative Underwater Vehicle Manipulator System
by Xinhui Zheng, Qiyan Tian and Qifeng Zhang
J. Mar. Sci. Eng. 2023, 11(3), 548; https://doi.org/10.3390/jmse11030548 - 3 Mar 2023
Cited by 9 | Viewed by 2401
Abstract
Recently, as humans have become increasingly interested in ocean resources, underwater vehicle-manipulator systems (UVMSs) have played an increasingly important role in ocean exploitation. To realize precise operation in underwater narrow spaces, the fly arm underwater vehicle manipulator system (FAUVMS) is proposed with manipulators [...] Read more.
Recently, as humans have become increasingly interested in ocean resources, underwater vehicle-manipulator systems (UVMSs) have played an increasingly important role in ocean exploitation. To realize precise operation in underwater narrow spaces, the fly arm underwater vehicle manipulator system (FAUVMS) is proposed with manipulators as its core. However, this system suffers severe dynamic coupling effects due to the combination of small vehicle and big manipulators. To resolve this issue, we propose a robust adaptive controller that contains two parts. In the first part, the extended Kalman filter (EKF) is designed to estimate the system states and predicts external disturbances to achieve adaptive control. In the second part, a chattering-free sliding mode control (SMC) is designed to converge the tracking errors to zero, thus guaranteeing the robustness of the controller. We constructed the simulation platform based on the geometric model of FAUVMS, and various simulations are carried out under different situations. Compared to the traditional methods, the proposed method has a faster convergent speed, a better robustness and adaptiveness to external disturbances, and the tracking errors of positions of the vehicle and each end-effector are much smaller. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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15 pages, 2654 KiB  
Article
Modeling and Adaptive Boundary Robust Control of Active Heave Compensation Systems
by Rui Du, Naige Wang and Hangyu Rao
J. Mar. Sci. Eng. 2023, 11(3), 484; https://doi.org/10.3390/jmse11030484 - 23 Feb 2023
Cited by 1 | Viewed by 1570
Abstract
Heave compensation systems are essential for operations’ safety, reliability, and efficiency in harsh offshore environments. This paper investigates the vibration suppression problem of a type of deep-sea robot with the length of time variation and harsh operating environments for active heave compensation systems, [...] Read more.
Heave compensation systems are essential for operations’ safety, reliability, and efficiency in harsh offshore environments. This paper investigates the vibration suppression problem of a type of deep-sea robot with the length of time variation and harsh operating environments for active heave compensation systems, where hydraulic heave compensators implement actuators with input nonlinearity, model coupling, and unknown nonlinear disturbances. A robust adaptive output feedback control scheme based on the backstepping control method is designed to eliminate deep-ocean robot vibration, where the adaptive law handles the system parameter uncertainty. Meanwhile, a nonlinear disturbance observer (NDO) is introduced to overcome the effects of random disturbances and model coupling. In addition, the stability of the whole system is proved according to Lyapunov’s theory, and the scheme is shown to be feasible by theoretical analysis. Finally, a comparative simulation study was conducted to validate the effectiveness of the proposed controller. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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11 pages, 3134 KiB  
Article
Underwater Optical Image Restoration Method for Natural/Artificial Light
by Tianchi Zhang, Qian Li, Yusong Li and Xing Liu
J. Mar. Sci. Eng. 2023, 11(3), 470; https://doi.org/10.3390/jmse11030470 - 22 Feb 2023
Cited by 3 | Viewed by 2495
Abstract
This paper investigates the underwater optical image restoration method under the background of underwater target detection based on optical vision in AUVs. The light source used for AUV detection is different when the AUV operates in different depths. The natural light source is [...] Read more.
This paper investigates the underwater optical image restoration method under the background of underwater target detection based on optical vision in AUVs. The light source used for AUV detection is different when the AUV operates in different depths. The natural light source is used in shallow water and the artificial light source is used in deep water. This paper investigates underwater optical image restoration in these two light conditions. Aiming at the problem of image blurring in underwater optical images, the traditional underwater image restoration method based on scattering model can obtain satisfactory image restoration performance in natural light conditions. However, it cannot obtain the same image restoration result in artificial light conditions. To solve this problem, this paper presents an improved underwater optical image restoration method based on the scattering model. The scattering model and power spectrum are used to solve the initial parameters of the filter, and the parameters are optimized based on an evaluation index. The index of image definition is introduced to evaluate the restoration performance and to achieve the satisfactory image restoration result in both natural light and artificial light conditions. The effectiveness of the presented method is verified by experiments. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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20 pages, 1272 KiB  
Article
Fixed-Time Average Consensus of a Dynamic Event-Triggered Mechanism in a System of Multiple Underactuated Autonomous Underwater Vehicles Based on a Body Frame Spherical Coordinate System
by Zhuo Wang, Ao Zhang, Hongde Qin and Shukai Jiang
J. Mar. Sci. Eng. 2023, 11(2), 385; https://doi.org/10.3390/jmse11020385 - 9 Feb 2023
Cited by 2 | Viewed by 1306
Abstract
This paper is concerned with the consensus of a system involving multiple underactuated autonomous underwater vehicles (AUVs). Combined with a dynamic event-triggered mechanism and a fixed-time stability theorem, the backstepping average consensus controllers are designed. Firstly, the new consensus control objective on the [...] Read more.
This paper is concerned with the consensus of a system involving multiple underactuated autonomous underwater vehicles (AUVs). Combined with a dynamic event-triggered mechanism and a fixed-time stability theorem, the backstepping average consensus controllers are designed. Firstly, the new consensus control objective on the system for multiple underactuated AUVs in a body frame (BF) spherical coordinate system is proposed, and the tracking error kinematic equations are established based on the kinematic characteristics of the underactuated AUV. The fixed-time consensus controller is designed by the backstepping method, and the average consensus theorem is proposed to improve the Lyapunov function. Furthermore, the dynamic event-triggered mechanism is adopted to reduce the communication requirements and energy consumption. This is the first solution to the problem of a consensus controller design for a system of multiple underactuated AUVs. Finally, numerical simulation results demonstrate that the proposed method has superior effectiveness over alternatives. Full article
(This article belongs to the Special Issue Advances in Underwater Robots for Intervention)
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