Article
Engineering, Marine
Hao Feng, Jiancheng Yu, Yan Huang, Jianan Qiao, Zhenyu Wang, Zongbo Xie, Kai Liu
Summary: The study proposes a method for detecting and tracking the thermocline using an AUV, which ensures coverage of the target thermocline over time and space through adaptive control. By evaluating the vertical thermocline distribution online, the method achieves coverage observation of a water column with multiple thermoclines.
Article
Engineering, Civil
Artur Wolek, James McMahon, Benjamin R. Dzikowicz, Brian H. Houston
Summary: This article describes the development and testing of a passive sonar, multitarget tracker, and adaptive behavior that enable an autonomous underwater vehicle (AUV) to detect and actively track nearby surface vessels. By repurposing a planar hull-mounted hydrophone array, the AUV can gather acoustic data and estimate the position and velocity of targets using a particle filter tracker. The tracking system is demonstrated through at-sea experiments.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2022)
Article
Engineering, Civil
Alessandro Bucci, Matteo Franchi, Alessandro Ridolfi, Nicola Secciani, Benedetto Allotta
Summary: Ensuring accurate navigation for an AUV is crucial for its surveillance, monitoring, and inspection missions. Most navigation filters for AUVs are based on Bayesian estimators and use instruments like Doppler velocity log. The use of payload sensors, such as cameras or forward-looking SONARs, has emerged as an interesting research field to reduce localization error drift. Two different frameworks, a centralized iterative UKF-based approach and a sensor fusion framework with parallel local UKFs, were implemented and compared.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2023)
Review
Engineering, Marine
John Zachary Nash, Jenny Bond, Michael Case, Ian McCarthy, Ryan Mowat, Iestyn Pierce, William Teahan
Summary: This paper provides a comprehensive review of using autonomous maritime robotics to track the fine scale movements of fish, showing a trend towards more complex systems and deep learning techniques. The results mainly focus on Autonomous Underwater Vehicles and suggest potential future research directions involving swarm intelligence methods.
Article
Automation & Control Systems
Xiang Cao, Lu Ren, Changyin Sun
Summary: This study proposes an autonomous underwater vehicle tracking control method based on trajectory prediction. Through advanced target detection algorithms and time profit Elman neural networks, accurate prediction and stable tracking of underwater dynamic targets are achieved.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Marine
Tu Lv, Mingjun Zhang, Yujia Wang
Summary: This paper proposes a prediction-based region tracking control scheme for an autonomous underwater vehicle (AUV) to solve the problems of overshoot and high energy consumption. By predicting the future position of AUV and the outer boundary of the desired region, the controller is designed accordingly. Furthermore, an optimization scheme considering the desired region is proposed to address the output saturation issue.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Civil
Trygve Olav Fossum, Petter Norgren, Ilker Fer, Frank Nilsen, Zoe Charlotte Koenig, Martin Ludvigsen
Summary: The article presents a method of detecting and sampling fronts using autonomous robotic vehicles in the Arctic region, with successful experiments conducted and yielding positive results.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2021)
Article
Robotics
Yingqiang Wang, Ruoyu Hu, S. H. Huang, Zhikun Wang, Peizhou Du, Wencheng Yang, Ying Chen
Summary: Underwater positioning is crucial for navigation and geo-referencing of AUVs. Traditional methods like GPS are not feasible in underwater environments, leading to the importance of acoustic methods like USBL positioning systems. However, the high cost and complexity of classical USBL systems hinder their widespread adoption, which is addressed by the piUSBL positioning method.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Huaitao Shi, Zelong Song, Xiaotian Bai, Ke Zhang
Summary: This paper proposes an attention mechanism-based multisensor data fusion neural network (MDFNN) for fault diagnosis of autonomous underwater vehicles (AUVs). The MDFNN utilizes a feature extraction layer and a feature fusion layer to optimize the model architecture and achieve high fault diagnosis accuracy.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Engineering, Electrical & Electronic
Shicheng Pei, Huan Wang, Te Han
Summary: This article introduces a time-efficient NAS-based AUV fault diagnosis framework (TENAS-FD), which can quickly search for excellent network architectures for AUV fault diagnosis. A novel scoring algorithm is constructed to evaluate the performance of untrained networks. Experimental results show that TENAS-FD has better diagnostic performance compared to hand-designing models.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Ensieh S. Hosseini, Moupali Chakraborty, Joshua Roe, Yvan Petillot, Ravinder Dahiya
Summary: This work presents the design and implementation of a porous PDMS-based flexible pressure sensor for autonomous underwater vehicles. The sensor shows linear response in air and near-linear response in water, with higher sensitivity in water. It also exhibits fast response and recovery time, as well as excellent repeatability and stability. The results demonstrate the suitability of the sensor for applications requiring a wide range of pressure, particularly in underwater robotics.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Marine
Zheyuan Wu, Qing Wang, Haocai Huang
Summary: This paper investigates a low-complexity tracking control method for autonomous underwater helicopters (AUH) without using nonlinear approximation strategies. It aims to ensure efficiency and high accuracy in dealing with environmental disturbances and modeling uncertainty. The introduction of Nussbaum function and shifting function solves the problem of unknown control direction and initial condition of system error. Additionally, an incremental event-triggered control mechanism with two thresholds is added to reduce the update rate of the controller and the mechanical loss of the thruster. Simulation results on AUHs demonstrate the effectiveness of the proposed scheme.
Article
Engineering, Civil
Yukiyasu Noguchi, Toshihiro Maki
Summary: This article introduces a method for tracking underwater structures using an AUV, based on stochastic means and utilizing commercial off-the-shelf sensors. It is suitable for surveying various underwater structures and is applicable to fast moving vehicles. The method has been successfully tested in both sea and tank environments, demonstrating its effectiveness in tracking rugged seafloors and vertical walls.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2021)
Article
Chemistry, Analytical
Yuhan Li, Ruizhi Ruan, Zupeng Zhou, Anqing Sun, Xiaonan Luo
Summary: This paper proposes a novel method for dynamically positioning an unmanned underwater vehicle (UUV) with unknown trajectories using an autonomous tracking buoy (PUVV-ATB) and ultra-short baseline measurements. The method utilizes a spatial location geometric model and divides the positioning process into four steps, including data preprocessing, direction capture, position tracking, and position synchronization. A new adaptive tracking control algorithm is introduced, which eliminates the need for trajectory prediction and is applied to the last three steps. The algorithm is implemented on the buoy for tracking simulation and sea trial experiments, demonstrating improved stability and precise tracking performance with a positioning error of less than 10 cm. This method breaks the assumption of trajectory prediction in traditional tracking control algorithms, providing a new direction for further research on UUV localization. Additionally, the conclusions of this paper have valuable reference for other UUV-related research and applications.
Article
Engineering, Marine
Francesco Ruscio, Riccardo Costanzi, Nuno Gracias, Josep Quintana, Rafael Garcia
Summary: Monitoring is crucial for marine environment preservation. This research proposes a framework that enables an autonomous underwater vehicle equipped with a down-looking camera to inspect the boundary of Posidonia oceanica meadows. The proposed solution utilizes machine learning and computer vision techniques to achieve this task.
Article
Business
Mario Paulo Brito, Ronald S. Lewis, Neil Bose, Gwyn Griffiths
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2019)
Article
Engineering, Marine
Yuting Jin, Shuhong Chai, Jonathan Duffy, Christopher Chin, Neil Bose
Article
Engineering, Marine
Yuting Jin, Shuhong Chai, Jonathan Duffy, Christopher Chin, Neil Bose
SHIPS AND OFFSHORE STRUCTURES
(2019)
Article
Public, Environmental & Occupational Health
Tzu Yang Loh, Mario P. Brito, Neil Bose, Jingjing Xu, Kiril Tenekedjiev
Article
Engineering, Marine
Jimin Hwang, Neil Bose, Hung Duc Nguyen, Guy Williams
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2020)
Article
Engineering, Marine
Yaomei Wang, Worakanok Thanyamanta, Craig Bulger, Neil Bose, Jimin Hwang
Summary: This research suggests using environmentally friendly gas bubble plumes as proxies for oil in field experiments, and tests the performance of a centrifugal-type microbubble generator in generating microbubble plumes. The study reveals the behavior of bubbles in deep water and estimates the residence time of bubble plumes, which can potentially serve as substitutes for oil plumes in future field trials of AUVs for delineating oil spills.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Marine
Yaomei Wang, Craig Bulger, Worakanok Thanyamanta, Neil Bose
Summary: Adaptive sampling offers an innovative approach to enhance the efficiency of underwater vehicles in data collection by utilizing sensor measurements and vehicle states. A backseat driver system was developed and tested on a Slocum glider, showcasing its ability to effectively control the vehicle through ROS interface.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
Jimin Hwang, Neil Bose, Hung Duc Nguyen, Guy Williams
Proceedings Paper
Computer Science, Theory & Methods
Guo Hao Ang, Shuangshuang Fan, Yuting Jin, HuiSheng Lim, Christopher K. H. Chin, Shuhong Chai, Neil Bose
2018 IEEE/OES AUTONOMOUS UNDERWATER VEHICLE WORKSHOP (AUV)
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Eonjoo Kim, Shuangshuang Fan, Neil Bose
2018 IEEE/OES AUTONOMOUS UNDERWATER VEHICLE WORKSHOP (AUV)
(2018)
Article
Computer Science, Information Systems
Eonjoo Kim, Shuangshuang Fan, Neil Bose