studies-rov

Studies of ROV concepts 2025 - Part B

Click on the octopus to return to the top of the page

1 - Control and Real-Time Monitoring of Autonomous Underwater Vehicle Through Underwater Wireless Optical Communication

Authors: Dongwook Jung, Rouchen Zhang, Hyunjoon Cho, Daehyeong Ji, Seunghyen Kim, and Hyeungsik Choi This paper introduces a new control structure using underwater wireless optical communication (UWOC) for autonomous underwater vehicle (AUV) motion control in underwater missions. The UWOC system transfers control inputs for the AUV's attitude from outside the water, while orientation data and visual images are sent to the control station outside the water. The system uses a return-to-zero modulation scheme for faster, longer- range data transfer. The hovering control performance of the AUV with the UWOC system was experimentally evaluated

4 - Wide Field-of-View Air-to-Water Rolling Shutter-Based Optical Camera Communication (OCC) Using CUDA Deep-Neural- Network Long-Short-Term-Memory (CuDNNLSTM)

Authors: Yung-Jie Chen, Yu-Han Lin, Guo-Liang Shih, Chi- Wai Chow, and Chien-Hung Yeh This work proposes a wide field-of-view (FOV) air-to-water OCC system using CUDA Deep-Neural-Network Long- Short-Term-Memory (CuDNNLSTM). The system can support a transmission rate of 7.2 kbit/s through a still water surface and 6.6 kbit/s through a wavy water surface, satisfying the hard-decision forward error correction (HD-FEC) bit-error-rate (BER).

5 - Model-Based AUV Path Planning Using Curriculum Learning and Deep Reinforcement Learning on a Simplified Electronic Navigation Chart

Authors: Lukasz Marchel, Rafał Kot, Piotr Szymak, and Paweł Piskur This paper evaluates reinforcement learning (RL)-based methods for autonomous underwater vehicles (AUVs) trajectory planning. It incorporates a full motion model and proposes a reward function to elicit desired behaviors. The models are trained on simplified ENC maps and compared against five classical methods. The proposed solution enables efficient, collision-free route planning.

6 - Enhanced Real-Time Simulation of ROV Attitude and Trajectory Under Ocean Current and Wake Disturbances

Authors: Yujing Zhao, Shipeng Xu, Xiaoben Zheng, Lisha Luo, Boyan Xu, and Chunru Xiong This study addresses issues in existing simulation systems for remotely operated underwater vehicles (ROVs) by developing a three-dimensional path simulation system for ocean inspection robots. The system optimizes the drag matrix by decomposing sea currents and simulating relative velocity in each direction. The system improves trajectory evolution stability and consistency, verifies control algorithm applicability, and provides reliable data support for ROV design and optimization. It also lays a solid foundation for developing intelligent underwater robots using IoT technology.

7 - Evaluation of the Nusantara 3 Remotely Operated Vehicle (N3- ROV): Special Report on Performance and Stability in Various Water Conditions

Authors: Xavercius Cezar Pratama, Indra Jaya, Muhammad Iqbal This study aimed to test the performance of the N3-ROV, a Remotely Operated Underwater Vehicle (ROV), in two different environments: a pool environment and a field environment. The N3-ROV had dimensions of 61x65x34 cm, 13 kg, and 128.4 kg.m/s² buoyancy. Performance tests showed that the N3-ROV had a straight movement in the pool environment with a 0° error, but had higher delay and error in the turning motion in the pool environment.

8 - A lightweight YOLO network using temporal features for high- resolution sonar segmentation

Authors: Sen Gao, Wei Guo, Gaofei Xu, Ben Liu, Yu Sun, and Bo Yuan A novel YOLO-based segmentation framework addresses the speed-accuracy trade-off in sonar image segmentation for autonomous underwater vehicles (AUVs). The framework uses a lightweight backbone network and bypass BiLSTM network for temporal feature learning, reducing processing latency and maintaining competitive segmentation accuracy..

9 - Three-Phase High Power Underwater Capacitive Wireless Power Transfer System for Autonomous Underwater Vehicles

Authors: Lei Yang, Liye Tian, Xinze Chen, Zhixue Bu, Dengrui Xing, Aimin Zhang, and Xiangqian Tong The paper presents a 1000 W high-frequency three-phase underwater capacitive wireless power transfer system for autonomous underwater vehicles (AUVs). The system's columnar structure and curved coupling coupler enhance mutual capacitance and power transfer capacity, reducing installation space and enhancing wireless power transfer capacity.

10 - Adaptive Event-Triggered Predictive Control for Agile Motion of Underwater Vehicles

Authors: Bo Wang, Junchao Peng, Jing Zhou, and Liming Zhao This paper explores the design and agile motion control of autonomous underwater vehicles (AUVs) in subsea environments. It uses Sequential Quadratic Programming (SQP) and Computational Fluid Dynamics (CFD) software to solve propeller arrangement optimization. The AET- NMPC algorithm significantly enhances response capability and control accuracy, reducing trajectory tracking error to 4.89%. This research provides insights for sophisticated underwater operations in challenging environments.

11 - Energy-Optimized Path Planning and Tracking Control Method for AUV Based on SOC State Estimation

Authors: Guangyi Yang, Zhenning Xu, Feng Wang, and Xiaoyu Zhang This paper proposes a path planning and trajectory tracking control framework for autonomous underwater vehicles (AUVs) combined with battery state of charge optimization. The framework uses the Grasshopper Optimization Algorithm (GOA) and the Artificial Potential Field Algorithm (APF) to achieve global path planning and local path optimization while minimizing energy consumption. The model predictive control (MPC) method ensures accurate tracking and dynamic management of SOC states. Simulation results show the framework outperforms traditional methods.

12 - Underwater SLAM Meets Deep Learning: Challenges, Multi- Sensor Integration, and Future Directions

Authors: Mohamed Heshmat, Lyes Saad Saoud, Muayad Abujabal, Atif Sultan, Mahmoud Elmezain, Lakmal Seneviratne, and Irfan Hussain This survey analyzes the latest developments in deep learning-enhanced SLAM for underwater applications, categorizing approaches based on methodologies, sensor dependencies, and integration with deep learning models. It highlights the benefits and limitations of existing techniques, highlights key innovations, and unresolved challenges. The survey introduces a novel classification framework for underwater SLAM based on its integration with underwater wireless sensor networks (UWSNs), enhancing localization, mapping, and real-time data sharing among AUVs. The survey identifies gaps in current research and suggests future directions for developing robust underwater SLAM solutions.

16 - Towards a Digital Twin for Open-Frame Underwater Vehicles Using Evolutionary Algorithms

Authors: Félix Orjales, Julián Rodríguez-Cortegoso, Enrique Fernández-Pérez, Alejandro Romero, and Vicente Diaz-Casas This paper proposes a comprehensive methodology for obtaining hydrodynamic coefficients of underwater vehicles, combining empirical measurements and evolutionary algorithms. The methodology is applied to a commercially available remotely operated vehicle, BlueROV2, and analyzed for its adequacy, including comparisons to the real vehicle.

17 - Navigation Control and Signal Processing Methods for Multiple Autonomous Unmanned Systems

Authors: Haoqian Huang, Bing Wang, and Yuan Yang This paper proposes a novel approach for underactuated autonomous underwater vehicles (AUVs) to improve formation control. By integrating Decision-Making (DO) with the formation controller, the system can handle nonlinear dynamics and ensure system stability. The approach addresses challenges such as assuming diagonal mass and damping matrices, relying on position measurements, and converge speed.

18 - Task Allocation and Path Planning Method for Unmanned Underwater Vehicles

Authors: Feng Liu, Wei Xu, Zhiwen Feng, Changdong Yu, Xiao Liang, Qun Su, and Jian Gao This study proposes a task allocation and path planning method for Unmanned Underwater Vehicles (UUVs) to improve their autonomous navigation and adaptability in complex marine environments. The method uses an Improved Grey Wolf Algorithm (IGWA) and a Circle chaotic mapping strategy to optimize task allocation and search efficiency. The GR-RRT* algorithm is employed for path planning, ensuring obstacle avoidance and reducing redundant sampling. Experimental results show significant advantages in task completion rate and path optimization efficiency.

19 - AUV Trajectory Planning for Optimized Sensor Data Collection in Internet of Underwater Things

Authors: Talal S. Almuzaini, and Andrey V. Savkin This paper presents a Value of Information (VoI)-based trajectory planning framework for a single Autonomous Underwater Vehicle (AUV) and an Unmanned Surface Vehicle (USV) to collect data from multiple Cluster Heads in an uneven seafloor. The approach uses a forward Dynamic Programming algorithm to optimize the AUV's trajectory and USV's start and end positions, maximizing residual VoI. Simulation results show the strategy outperforms conventional baselines for effective data collection in challenging underwater environments.

20 - Hydrodynamic Calculation and Analysis of a Complex-Shaped ROV Moving near the Wall Based on CFDs

Authors: Mengjie Jiang, Chaohe Chen, Zhijia Suo and Yingkai Dong A study using computational fluid dynamics (CFDs) analyzes the hydrodynamic characteristics of remotely operated vehicles (ROVs) near walls, considering factors like structural asymmetry, speed, and distance. Results show that wall influence on hydrodynamic forces is significant, with pressure differential resistance being the dominant factor affecting performance. This provides insights into calculating hydrodynamic coefficients and modeling complex shapes operating near walls.

21 - Better interaction experience: human-machine interface for soft robotic systems

Authors: Zeyu Gao, Zhiyuan Liao, Chunquan Li Soft robots are emerging as a key robotics technology due to their soft materials and unique drive methods. They adapt to unstructured environments and interact with humans safely, opening new directions in robotics development. Sensor performance plays a crucial role in human-machine interface (HMI), and new materials and technologies refine HMI, enhancing soft robot systems' possibilities.

22 - Hierarchical Adaptive Fixed-Time Formation Control for Multiple Underactuated Autonomous Underwater Vehicles Under Uncertain Disturbances and Input Saturation

Authors: Jiacheng Chang, Lanyong Zhang, Yifan Tan, Xue Fu, and Hongjun Yu This paper proposes a novel hierarchical framework for adaptive fixed-time formation control for multiple autonomous underwater vehicles (AUVs). The framework divides formation requirements and individual control challenges into two layers: Collision-free Formation Trajectories Generation (CFTG) and Adaptive Trajec-tories Tracking (ATT). The CFTG layer uses a consensus-based controller, an improved artificial potential field method, and an auxiliary compensation system to meet complex formation tasks. Simulations demonstrate the effectiveness and performance of the proposed method.

23 - ROVs Utilized in Communication and Remote Control Integration Technologies for Smart Ocean Aquaculture Monitoring Systems

Authors: Yen-Hsiang Liao, Chao-Feng Shih, Jia-Jhen Wu, Yu-Xiang Wu, Chun-Hsiang Yang, and Chung- Cheng Chang This study presents an intelligent aquatic farming surveillance system that integrates remotely operated vehicles, sensors, and real-time data transmission. It uses a mobile communication architecture with buoy relay stations for distributed edge computing, supports future upgrades to Beyond 5G and satellite networks, features a multi-terminal control system for monitoring anytime, anywhere, and is cost-effective. The system has successfully processed 324,800 data transmission events, demonstrating excellent performance in real-world production environments. It reduces operating costs and improves aquaculture efficiency.

24 - Energy-Optimized Path Planning for Fully Actuated AUVs in Complex 3D Environments

Authors: Shuo Liu, Zhengfei Wang, Tao Wang, Shanmin Zhou, Yu Zhang, Pengji Jin, and Guanjun Yang This paper presents an energy-optimized path planning approach for fully actuated autonomous underwater vehicles (AUVs) in three-dimensional ocean environments. It uses real terrain data and environmental models to develop a mathematical model of the AUV's total energy consumption. The proposed algorithm combines EOPSO and QP to identify the optimal path and surge speed, demonstrating superior robustness and optimized energy consumption.

25 - Enhanced AUV Autonomy Through Fused Energy-Optimized Path Planning and Deep Reinforcement Learning for Integrated Navigation and Dynamic Obstacle Detection

Authors: Kaijie Zhang, Yuchen Ye, Kaihao Chen, Zao Li, and Kangshun This paper introduces a hybrid framework that combines a Multithreaded Energy-Optimized Batch Informed Trees (MEO-BIT*) algorithm with Deep Q-Networks (DQN) to improve autonomous underwater vehicles (AUVs) in dynamic environments. The MEO-BIT* component provides efficient global path planning, while the DQN component facilitates dynamic obstacle detection and adaptive local navigation. Experimental validation in asimulated Achao waterway (Chile) demonstrated the system's superiority, achieving a 46% reduction in collision rates, 15.7% improvement in path smoothness, and 78.9% faster execution time compared to conventional methods..

26 - Pectoral Fin-Assisted Braking and Agile Turning: A Biomimetic Approach to Improve Underwater Robot Maneuverability

Authors: Qu He, Yunpeng Zhu, Weikun Li, Weicheng Cui, and Dixia Fan The study investigates the integration of biomimetic pectoral fins into SpineWave robotic fins, enhancing maneuverability, stability, and braking efficiency in underwater robotics. The 1-DOF pectoral fin mechanism reduces stopping distance by 50%, enhancing agility and control, and laying the groundwork for adaptive fin designs and real-time control strategies.

27 - Multi-Information-Assisted Bistatic Active Sonar Target Tracking for Autonomous Underwater Vehicles in Shallow Water

Authors: Zhanpeng Bao, Yonglin Zhang, Yupeng Tai, Jun Wang, Haibin Wang, Chao Li, Chenghao Hu, and Peng Zhang This paper proposes a multi-information-assisted target tracking algorithm for bistatic active sonar, leveraging spatial and temporal echo signal structures to improve underwater surveillance for autonomous underwater vehicles (AUVs). The algorithm integrates target position, echo amplitude, and Doppler information during AUV movement, improving association probability computation efficiency. The algorithm shows a 23.95% performance improvement over traditional probabilistic data association, enhancing tracking autonomy and advancing AUVs' capability in ocean engineering applications.

13 - An effective fault-tolerant control with slime mold algorithm for unmanned underwater vehicle

Authors: Tianhong Zeng, Daqi Zhu, Chunhua Gu, Simon X. Yang This article discusses a novel fault-tolerant control strategy known as the Slime Mold Algorithm (FTC-SMA) designed to improve the resilience of multi-thruster unmanned underwater vehicles during thrust loss events. This strategy facilitates rapid thrust redistribution to maintain torque and sailing direction, even under severe propulsion system failures. By adhering to physical thruster limits, FTC-SMA effectively addresses over-actuation problems. The article validates the strategy’s effectiveness, efficiency, and stability through various simulation experiments, showcasing its superiority compared to existing algorithms like particle swarm optimization and grasshopper optimization.

32 - A systematic review of haptic texture reproduction technology

Authors: Si Chen, Tonghe Yuan, Lujin Xu, Weimin Ru, Dongqing Wang This article highlights techniques such as vibration, ultrasound, and electrostatic systems, and investigates the role of artificial intelligence and deep learning in enhancing the personalization of tactile feedback. The significance of understanding tactile perception mechanisms, specifically the function of Piezo proteins and the interaction between receptors and their environments, is emphasized for improving the accuracy of feedback systems. Moreover, challenges in accurately reproducing fine textures and high-frequency vibrations are addressed, pointing to the necessity of interdisciplinary research in fields like neuroscience, materials science, and AI for future progress in haptic technology.

33 - Environment sensing technology of underwater ROV based on artificial siding

Authors: Wenhui Wang, Fumeng Ye, & Rufei He This article discusses the limitations posed by high pressure and low temperature in underwater environments on sensor performance, leading to measurement inaccuracies. It introduces a novel underwater sensing technology for ROVs based on artificial side lines, detailing the terrain perception principles, parameter analysis, and the construction of an acoustic sensor network. This method significantly enhances environment perception accuracy, with measurement errors under 1% under various conditions. This technology shows promise for several applications, including underwater exploration and marine research, with suggestions for ongoing optimization and incorporation of additional environmental parameters

36 - The use of emerging autonomous technologies for ocean monitoring: insights and legal challenges

Authors: Aspasia Pastra, Tafsir Matin Johansson, Joana Soares, and Frank E. Muller-Karger This article explores the crucial function of Essential Ocean Variables (EOVs) in enhancing the understanding of marine ecosystems and emphasizes the importance of advanced observation technologies like Autonomous Underwater Vehicles (AUVs), Unmanned Aerial Vehicles (UAVs), and Maritime Autonomous Vehicles (MAVs). It highlights the significant legal and policy challenges associated with the integration of these technologies into Marine Scientific Research (MSR), identifying six key legal areas needing attention. To address these challenges effectively, the article advocates for a coordinated approach involving scientists, policymakers, and international organizations.

37 - Towards Autonomous Coordination of Two I-AUVs in Submarine Pipeline Assembly

Authors: Salvador López-Barajas, Alejandro Solis, Raúl Marín-Prades, Pedro J. Sanz The article explores the challenges in conducting inspection, maintenance, and repair (IMR) operations on underwater infrastructure, highlighting the limitations of remote-operated vehicles (ROVs) and professional divers. It introduces an innovative autonomous dual-I-AUV (Intervention-Autonomous Underwater Vehicle) system designed for the assembly of rigid pipeline segments in confined underwater environments. The system comprises two I-AUVs equipped with advanced manipulators that work in coordination to perform precise underwater tasks, demonstrating successful trials in a controlled water tank, which marks progress towards automated subsea construction.

2 - Smooth and efficient motion planning of large-scale and cooperative multi-arm tunnel drilling robot

Authors: Yuming Cui, Jiajun Pu, Ningning Hu, Menghao Cui To address the motion planning challenges in multi-arm cooperative operations of tunnel rock-drilling robots, the document’s authors established forward/inverse kinematics models for drilling arms using an enhanced Denavit-Hartenberg method combined with radial basis function neural networks. A joint-space collision avoidance strategy is proposed using an enhanced artificial potential field (IAPF) method that incorporates both attractive and repulsive potential fields.

3 - Joint optimization of AoI and energy for AUV-assisted data collection in underwater acoustic sensor networks

Authors: Weinan Cao, Keyu Chen, and En Cheng For the sake of jointly optimizing the age of information (AoI) and energy consumption, we propose a multi- autonomous underwater vehicle (AUV)-assisted underwater data collection scheme in this paper. Simulation results show that the proposed algorithm outperforms three benchmark algorithms in terms of average AoI and collection utility. Additionally, the energy consumption of sensor nodes is more balanced, and the network lifetime is extended.

15 - Long-Endurance Collaborative Search and Rescue Based on Maritime Unmanned Systems and Deep-Reinforcement Learning

Authors: Pengyan Dong, Jiahong Liu, Hang Tao, Yang Zhao, Zhijie Feng, and Hanjiang Luo This paper proposes a long-endurance collaborative search and rescue (SAR) scheme for maritime unmanned systems, integrating UAVs and USVs to leverage their complementary vision-sensing capabilities—UAVs for wide-area aerial surveillance and USVs for precise surface- level operations. A multi-agent reinforcement learning (MARL)-based approach enables UAV swarms to conduct cooperative first-phase search using probabilistic maps, while USVs refine these maps for accurate second-phase localization. To overcome UAV energy limitations, a MARL-driven multi-USV charging scheduling method is introduced to extend UAV flight time.

35 - Hydrodynamic Numerical Analysis of AUV Underwater Docking with Conical Docking Bay

Authors: Yang Gao, Xiaohu Li, Jianwei Mei, Daohua Lu, and Yanbing Tang This paper analyzes how docking geometry parameters and ocean currents affect the hydrodynamics of an autonomous underwater vehicle (AUV) during underwater docking with a conical bay. Using a 3D mathematical model and CFD methods, the study examines impacts on docking resistance, lift, velocity, and pressure fields. Key findings include: a larger taper angle reduces drag, while a wider inlet diameter increases it; higher current speeds amplify drag variations, and greater direction angles create significant lift due to velocity differences between upper and lower flow fields. The results offer theoretical insights for optimizing AUV docking structures and control strategies.

Click here

14 - A 3D adaptive spiral coverage path planning algorithm of autonomous underwater vehicle for enhanced edge-corner coverage

Authors: Zhaoye Chen, Jiaxin Gao, Jiahui Ma, and Xiang Wang Underwater acoustic sensor networks (UASNs) are critical for marine applications like data acquisition and disaster prevention, where autonomous underwater vehicles (AUVs) act as mobile anchor nodes to locate and communicate with sensor nodes. A key challenge is ensuring AUVs cover all nodes, particularly in high-density edge-corner areas influenced by ocean currents. Traditional coverage path planning (CPP) algorithms often struggle in these regions, leading to poor performance. This paper introduces the adaptive spiral CPP (AS-CPP) for 3D marine environments, using a dynamic spiral model that adjusts path shape and radius based on node density to improve coverage and energy efficiency.

28 - Design and hydrodynamic coefficient identification of deep-sea unmanned underwater vehicles

Authors: Houyuan Hua, Zhen Zhang, Huarui Wang, Wenjing Yu Underwater Acoustic Sensor Networks (UASNs) utilize Autonomous Underwater Vehicles (AUVs) as mobile anchor nodes for tasks like ocean data acquisition and disaster prevention. However, uneven node distribution, particularly in high-density edge-corner areas, challenges traditional path planning algorithms (CPPs), which often underperform in such regions. This paper introduces the Adaptive Spiral CPP (AS-CPP) for 3D marine environments, featuring a density-adaptive spiral model to optimize edge-corner coverage while minimizing energy use.

29 - LQR-Based Tracking Control for Remotely Operated Vehicles: A Co-Simulation Framework for Sustainable Environmental Monitoring

Authors: Hoai Thanh Nguyen, Van Qui Nguyen, Hoang Quan Vo, Van Thuyen Ngo, Duc Thien Tran This paper introduces a tracking controller for a remotely operated underwater vehicle (ROV), specifically for the BlueROV2. It employs linear quadratic regulator (LQR) tracking based on the ROV's dynamic model. A co- simulation environment using MATLAB and Gazebo is developed to test the control system, showing improved stability and tracking performance. Additionally, a hardware-in-the-loop simulation (HILS) platform is used to evaluate teleoperation controllability, confirming that the LQR tracking controller enhances stability and responsiveness under complex underwater conditions.

30 - Octopus-Inspired Self-Adaptive Hydrogel Gripper Capable of Manipulating Ultra-Soft Objects

Authors: Yixian Wang, Desheng Liu, Danli Hu, Chao Wang, Zonggang Li, Jiayu Wu, Pan Jiang, Xingxing Yang, Changcheng Bai, hongying Ji, Xin Jia, Xiaolong Wang Octopuses grasp objects gently with flexible suckers, yet current soft grippers struggle with delicate underwater items. Inspired by octopus infundibulum and tentacles, a hydraulically actuated hydrogel gripper was developed via supramolecular hydrogels and 3D printing, featuring a tunable curvature membrane for switchable adhesion. It successfully handles fragile foods like egg yolks and enables underwater robot station-keeping and crawling, offering a new design strategy for marine soft robotics.

31 - A holographic GRIN lens for broadband, highly directive, and aberration-free echo detection

Authors: Jinhu Zhang, Sheng Liu, Chen Yang, Nana Zhou, Erqian Dong, Zhenxuan Bu, Wei Zheng, Fei Zhang, Zhongchang Song, and Yu Zhang Directing waves through aberrating media challenges underwater acoustics, as AUV domes distort sonar beams and reduce detection range. We present a passive broadband holographic gradient-index lens of stable tungsten-silicone metamaterial, designed via time-reversal and high-frequency principles. Operating at 20–45 kHz, it corrects aberrations, sharpens beams four-fold (65° to 16°–30°), raises source level >10 dB, suppresses reverberation >10 dB, and extends range, establishing a versatile wavefront engineering platform.

34 - Development of a turning control strategy for a bio-inspired underwater vehicle

Authors: Owen McKenney, Joseph Zhu, Tianjun Han, and Hilary Bart-Smith This study presents a single-actuator turning strategy for the Tunabot using asymmetric tail-beat timing, inspired by tuna kinematics. Stroke duration is modified via one motor synchronized by an encoder. Tank experiments with high- speed video and DeepLabCut tracking yielded a 1.42 body-length turning radius at 66% asymmetry. Scaling laws predict radius and speed, while power comparisons show efficiency versus symmetric maneuvers, enabling maneuverable BUVs without dedicated steering.