studies-rov-concepts_2022-b

Studies of ROV concepts 2022 - Part B

Date of publication: 2022 Authors: D. Ross Robertson, Luke Tornabene, Claudia C. Lardizabal, & Carole C. Baldwin. This paper intents to prove that submersibles can efficiently collect reef fishes of a broad range of taxa, ecotypes, and sizes, leading to a more comprehensive understanding of the regional GC deep-reef fish fauna.

18 - Hydrodynamic performance of open-frame deep sea remotely operated vehicles based on computational fluid dynamics method,

Date of publication: 2022 Authors: Qianrong Li & Baoji Zhang The resistance performance and motion stability of deep-sea remotely operated vehicles (ROVs) subjected to underwater motion conditions are based on the unsteady Reynolds-averaged Navier-Stokes method combined with the six-degree-of-freedom equation of motion to quickly and accurately predict them. In the modeling process, the authors consider the complexity of ROV geometry and thus reduce the model to a series of regular geometries to maximize the position and weight of the original components.

Authors: Samuel M. Youssef, MennaAllah Soliman, Mahmood A. Saleh, Mostafa A. Mousa, Mahmoud Elsamanty, & Ahmed G. Radwan. Nature and biological creatures are sources of inspiration. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, focusing on the underwater application frontier.

Authors: Bing Sun, Wen Pang, Mingzhi Chen, Daqi Zhu This paper presents the design of a new type of search and rescue remotely operated vehicle (ROV) system. The goal is to achieve the underwater target search and detection and small target capture and rescue operation requirements. First, the overall design of the whole underwater surface system and the layout design of the propulsion system are given.

Authors: Alexander Konoplin, Nikita Konoplin, and Alexander Yurmanov This article considers the issues of development of a smart system for supporting activities of ROV operators and its practical implementation for the efficient operation of a ROV Comanche 18 that is based on the R/V Akademik M.A. Lavrentiev. The system uses algorithms that provide coordinated movements of the ROV and its depressor unit. These algorithms are designed for ROVs to make synchronous, accurate, and accident-free movements along long-distance routes even when launched from a support vessel without dynamic positioning (DP).

Authors: Malte von Benzon, Jesper Liniger, Fredrik Fogh Sørensen, Simon Pedersen Marine growth on offshore underwater structures is a problem as it reduces the lifespan. The structures are cleaned annually by manually operated ROVs. Automation of these ROVs can improve the removal efficiency, and thereby reduce the cleaning campaign time and cost, as it is challenging for the operators to manually stabilize the ROVs under the harsh off shore conditions. Waves, ocean currents, the attached tether and the cleaning tool all generate external forces to the ROVs acting as substantial disturbances which can be rejected by a controller. This study examines the operating range of a standard compact ROV subject to external disturbances.

Authors: Yanhu Chen, Luning Zhang, & Yucheng Ling This study proposes an underwater free-space optical communication method of transmitting information. The characteristics of underwater optical transmission and the photoelectric signal processing and modulation and demodulation algorithms are studied and modeled.

Authors: Ioannis Polymenis, Maryam Haroutunian, Rose Norman, & David Trodden There have been recent breakthroughs in Artifcial Intelligence (AI) and, notably, Deep Learning (DL) models and applications. These have widespread usage in various fields, including unmanned aerial vehicles and autonomous vehicles, car navigation, and other applications. However, they are not as prevalent in underwater applications due to the difficulty of obtaining underwater datasets for a specific application. In this sense, the current study utilizes recent advancements in DL to construct a bespoke dataset generated from photographs of items captured in a laboratory environment.

Authors: Tingjun Lei, Guoming Li, Chaomin Luo, Li Zhang, Lantao Liu, & Richard Stephen Gates Many real-world robot applications in precision agriculture, poultry farms, disaster response, and environment monitoring require search, locate, and removal (SLR) operations by autonomous mobile robots. In such application settings, the robots initially search and explore the entire workspace to find the targets so that the subsequent robots conveniently move directly to the targets to fulfill the task. A multi-layer robot navigation system is necessary for SLR operations. The scenario of interest is the removal of broiler mortality by autonomous robots in poultry barns in this paper.

Authors: Ruiheng Liao, Wei Su, Xiurong Wu, & En Cheng Unmanned underwater vehicles (UUVs) that are widely utilized for underwater environment detection and underwater resource exploration have to be localized by underwater acoustic sensor networks (UASNs). However, localization accuracy is hard to guarantee due to the limited bandwidths, long propagation latency, and limited energy resources of the UASNs. This paper proposes a reinforcement learning (RL) and neural network-based mobile underwater localization scheme to optimize the anchor node selection in the UASNs to localize the target precisely.

Authors: Chao-Lin Kuo , Yu-Chi Pu, and Qi-An Chen 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, the authors 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.

Authors: Zhenjing Zhu, Ning Hu, Junyi Wu, Wenxin Li, Jiabao Zhao, Maofa Wang, Fanzong Zeng, Huajie Dai, and Yongju Zheng. Researchers use underwater acoustic equipment to explore the unknown ocean environment, which is one of the important means to understand and utilize the ocean. For underwater acoustic equipment, the application of underwater acoustic metamaterials is the premise to ensure and improve the performance of underwater acoustic communication, acoustic stealth, and sonar detection.

Authors: Yongji Zhang, Yu Jiang, Hong Qi, Minghao hao, Yuehang Wang, Kai Wang, Fenglin We The marine environment presents unique challenges for human–robot interaction. Communicating with gestures is a common way for interacting between the diver and autonomous underwater vehicles (AUVs). However, underwater gesture recognition is a challenging visual task for AUVs due to light refraction and wavelength color attenuation issues. Current gesture recognition methods classify the whole image directly or locate the hand position first and then classify the hand features. Among these purely visual approaches, textual information is largely ignored. This paper proposes a visual–textual model for underwater hand gesture recognition (VT-UHGR).

Authors: Yalçın Ata, Hanaa Abumarshoud, Lina Bariah, Sami Muhaidat, and Muhammad Ali Imran Intelligent reflecting surfaces (IRSs) offer a paradigm shift towards enhancing wireless communications capabilities. Using this emerging technology in underwater wireless systems is a promising solution to overcome the limitations pertinent to such challenging environments. In this paper, we quantify the performance enhancement offered by integrating IRS technology in the context of underwater optical wireless communication (OWC). Specifically, the authors derive a closed-form expression for the outage probability over log-normal channels, considering the underwater attenuation, pointing error, and turbulence effects.

Authors: Ali F.Kaeib, Omar .A. Alshawish, Suhayl Ali Altayf, Mohammed A. Gamoudi Underwater wireless communications have more attention daily due to their wide applications in the military and the scientific community. It is also useful in vehicles and devices deployed underwater, which are challenging to connect with wires. Acoustic communications mostly use underwater technology nowadays, which suffers from limited bandwidth and capacity. For this reason, complementary technology like underwater wireless optical communication (UOWC) will be in the field. This paper simulated the UOWC system with Optisystem software to measure the maximum distances in different underwater mediums.

Authors: Le Yu, Han Sun, Shangwei Su, Huixuan Tang, Hao Sun, and Xiaoyu Zhang Based on the analysis of the development status of underwater wireless power transmission technology, this paper puts forward the challenges of underwater wireless power transmission, and summarizes the electromagnetic coupler structure, underwater docking mode, compensation topology, control method, and eddy current loss. The present research hotspots in the field of underwater wireless power transmission are summarized and analyzed. Finally, according to the development trend of technology, the urgent technical problems in underwater wireless power transmission are expounded.

Authors: Tao Yan, Zhe Xu, Simon X. Yang, S. Andrew Gadsden This paper presents a comprehensive overview of recent developments in formation control of multiple autonomous underwater vehicles (AUVs). Several commonly used structures and approaches for formation coordination are listed, and the advantages and deficiencies of each method are discussed. The difficulties confronted in synthesis of a practical AUVs formation system are clarified and analyzed in terms of the characteristic of AUVs, adverse underwater environments, and communication constraints. The state-of-the-art solutions available for addressing these challenges are reviewed comprehensively.

Authors: Dianyu Yang, Chensheng Cheng, Can Wang, Guang Pan and Feihu Zhang The AUV (Autonomous Underwater Vehicle) navigation process relies on the interaction of a variety of sensors. The side-scan sonar can collect underwater images and obtain semantic underwater environment information after processing, which will help improve the ability of AUV autonomous navigation. However, there is no practical method to utilize the semantic information of side scan sonar image. A new convolutional neural network model is proposed to solve this problem in this paper.

31 - Design, Simulation, and Experimental Study on the Hydraulic Drive System of an AUV Docking Device with Multi-Degree Freedom

Authors: Xiaofei Du, Chaoyong Zong, Bo Zhang, and Maolin Shi AUV docking devices have the ability to achieve homing of the AUV, supply the AUV with energy, and exchange data with it, thus improving the endurance and ensuring the continuous long-term and large scale operation of the AUV. To improve the successful docking rate of the AUV, a funnel-shaped underwater docking device with multi- degree freedom based on a deep-sea platform was designed in this paper.

Authors: Sean T. Frey, A. B. M. Tahidul Haque, Ravi Tutika,Elizabeth V. Krotz, Chanhong Lee, Cole B. Haverkamp, Eric J. Markvicka , Michael D. Bartlett Cephalopods, such as the octopus, use suckers to generate adhesion and suction forces. Their grippers are particularly attractive for underwater gripping, as the adhesives are reversible, attachments can be activated quickly, and adhesion can be achieved on diverse substrates under both dry and wet conditions.

Authors: Xiaonan Huang, Zach J. Patterson, Andrew P. Sabelhaus, Weicheng Huang, Kiyn Chin, Zhijian Ren, Mohammad Khalid Jawed, and Carmel Majidi Despite tremendous progress in the development of untethered soft robots in recent years, existing systems lack the mobility, model-based control, and motion planning capabilities of their piecewise rigid counterparts. This study introduces a framework for physics-based modeling, motion planning, and control of a fully untethered swimming soft robot.

20 - An Embedded Tactical Decision Aid Framework for Environmentally Adaptive Autonomous Underwater Vehicle Communication and Navigation

Authors: EeShan C. Bhatt, Bradley Howard, and Henrik Schmidt This article presents a tactical decision-aid framework for a human decision-maker collaborating with an autonomous underwater vehicle (AUV) to integrate the vertical sound speed profile for underwater navigation and communication. During the pre-deployment phase, the authors use modeled and real oceanographic data. They load basis function representations of the sound-speed perturbations onto one or more AUVs on deck, where a handful of weights can estimate a sound-speed profile.

Authors: David Herrero-Pérez, Humberto Martínez-Barberá Underwater manipulation with current robotics technology is a challenging task with significant limitations in versatility and robustness terms. Such functionality has tremendous potential covering a broad spectrum of applications, mainly replacing divers performing hazardous jobs. Soft robotics provide an efficient solution for operating in these scenarios and adapting to uncertain environmental conditions. This paper presents the design and fabrication of a simple, low-cost, and easily deployable soft gripper for underwater manipulation.

Authors: Miao Zhang, Haibao Hu, Peng Du, Xiaopeng Chen, Zhuoyue Li, Chao Wang, Lu Cheng, Zijian Tang This document proposes a new hydrodynamic artificial intelligence (AI) detection method to achieve accurate detection of “Internal Solitary Waves (ISWs)” by an underwater vehicle. Two deep convolutional neural network structures are established to predict the relative position between the underwater vehicle and ISW and the flow field around the underwater vehicle. Combining field observation data and the computational fluid dynamics (CFD) method achieves accurate numerical simulation of the motion of the underwater vehicle in a real ISW environment.

Authors: Chang Shi, Xide Cheng, Zuyuan Liu, Kunyu Han, Penghui Liu, and Long Jiang Disturbance is generated, and a wake remains that destroys the original free surface and produces a new wake when a vehicle moves underwater. To study the mechanism and characteristics of the wave-making wake generated by the maneuvering motion of an underwater vehicle in density-stratified fluid, the k-E model and the VOF method based on the RANS equation were used in this paper to analyze the SUBOFF model in stratified fluid at different drift angles.

Authors: Hao Cao, and Lihua Wen This paper presents the results of research on the noise generated by an underwater vehicle in its operational state. The study combines the large eddy simulation turbulence model and Lighthill’s acoustic analogy theory and extracts the transient flow field data as the excitation conditions for acoustic calculations. The results of the numerical calculations of the external acoustic field were obtained under the vehicle wall pressure pulsation, Lighthill volume excitation condition, and the vibration excitation condition of the underwater vehicle.

Authors: Leif Christensen, José de Gea Fernández, Marc Hildebrandt, Christian Ernst, Siegfried Koch, Bilal Wehbe The objective of this manuscript is to scrutinize the latest advancements in underwater robotics with a particular emphasis on the utilization of artificial intelligence (AI) for model learning, robot control, perception,navigation, as well as manipulation.

Authors: Chin-Chun Chang, Naomi A. Ubina, Shyi-Chyi Cheng, Hsun-Yu Lan, Kuan-Chu Chen, and Chin-Chao Huang This paper introduces a dual-mode underwater surveillance camera system that includes a sonar imaging device and a stereo camera. The sonar component is equipped with cloud-based AI capabilities that can accurately calculate the number, distribution, and size of fish within a dense school.

Authors: Antoni Burguera, and Francisco Bonin-Font Recent studies show that machine learning, especially deep learning, is effective in dealing with uncertainties in underwater sensing. Despite their success in their respective fields, the combination of machine learning and underwater robotics has not been thoroughly explored. This paper focuses on merging these fields and explores the potential for machine learning to enhance underwater robotics.

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Authors: Bing Sun, Wen Pang, Mingzhi Chen, Daqi Zhu This document describes the design and development of a new type of search and rescue remotely operated vehicle (ROV) system. It outlines the goals, design process, and testing phases of the ROV and emphasizes its capabilities in underwater target search, detection, and small target capture and rescue operations.

Authors: Jiabao Zhao, Ning Hu, Junyi Wu, Wenxin Li, Zhenjing Zhu, Maofa Wang, Yongju Zheng, and Huajie Dai This paper reviews the current applications and future prospects of piezoelectric metamaterials in underwater equipment. It discusses the challenges faced by traditional materials in marine environments and highlights the advantages of using piezoelectric metamaterials for sound insulation and energy conversion, providing an overview of the advancements and potential developments in this field.

Authors: Eito Sato, Hailong Liu, Yasuaki Orita, Norimitsu Sakagami, and Takahiro Wada This study focused on developing and evaluating a cooperative path-following control method for remotely operated underwater vehicles (ROVs) to reduce the workload of human operators by assisting with automatic control, allowing them to allocate more attention to visual inspection tasks. It describes the methodology, experiment, and results, highlighting the effectiveness of the proposed method in improving task performance and reducing operator workload compared to manual control.

1 - Model Establishment and Parameter Identification of Remotely Operated Vehicle (ROV).

Author: Yelei Zhang, Baoji Yin, Huifeng Jiao, Jian Zhang, and Fei Yan To study the dynamic characteristics of remotely operated vehicle (ROV) underwater motion, a transformation matrix was created, and the ROV's dynamics model was derived using the Newton-Euler equation. The dynamic model was simplified based on various characteristics. Pool experiments used the least squares method to identify parameters of dynamic models, comparing results with the same control signals. Error analysis showed small errors between theoretical and experimental values, confirming the model's accuracy.

06 - Increasing the autonomy of an underwater ROV

Author: Marko Vuksic, Tonko Kovacevic, Barbara Dzaja, Predrag Dukie, Slaven Sitie, Hai Nam Tran, Vincent Rodin, Laurent Lemarchand, Valérie- Anne Nicolas, Alain Plantec, Stéphane Rubini, Frank Singhoff Small presentation illustrating parts of ROVs that can be optimized

21 - A Low-Delay Source-Location-Privacy Protection Scheme with Multi-AUV Collaboration for Underwater Acoustic Sensor Networks.

Authors: Xiaojing Tian, Xiujuan Du, Xiuxiu Liu, Lijuan Wang, Lei Zhao To protect source-location-privacy (SLP) in underwater acoustic sensor networks (UASNs), a new low-delay scheme called LDSLP-MA is proposed. It uses multipath routing and multi-autonomous underwater vehicle (AUV) collaboration to enhance protection while minimizing delay. The scheme shows improved safety, reduced energy use, and lower delays compared to existing methods.

08 - Joint elasticity produces energy efficiency in underwater locomotion: Verification with deep reinforcement learning

Author: Chu Zheng, Guanda Li, and Mitsuhiro Hayashibe Underwater snake robots face challenges in designing energy-efficient gaits due to their unique mechanics and locomotion patterns. A deep reinforcement learning and curriculum learning method is proposed for underwater snake robot gait design. The method compares the gait generated by a conventional parametric gait equation controller with elasticity in the robot's joints. The deep reinforcement learning controller produces a more energy-efficient gait than the gait equation controller, maximizing energy efficiency and achieving maximum velocity.