Results 71 to 80 of about 1,858 (201)

Study on the Optimal Design of a Shark-like Shape AUV Based on the CFD Method

Journal of Marine Science and Engineering, 2023
In previous AUV designs, the thrusters were often placed outside the vehicle, resulting in their performance being significantly influenced by the shape of the vehicle.
Yu Lu, Jianping Yuan, Qiaorui Si, Peifeng Ji, Ding Tian, Jinfeng Liu   +5 more
doaj   +1 more source

Autonomous four-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle [PDF]

, 2015
© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Field Robotics 33 (2016): 67-81, doi:10.1002/rob.21617Coastal upwelling is a wind-driven ...
Bellingham, James G., Kieft, Brian, Ryan, John P., Stanway, Michael J., Zhang, Yanwu   +4 more
core   +1 more source

Reviewing seas of data: Integrating image‐based bio‐logging and artificial intelligence to enhance marine conservation

Methods in Ecology and Evolution, Volume 17, Issue 2, Page 272-290, February 2026.
Abstract Conservation of marine ecosystems can be improved through a better understanding of ecosystem functioning, particularly the cryptic underwater behaviours and interactions of marine predators. Image‐based bio‐logging devices (including images, videos and active acoustic) are increasingly used to monitor wildlife movements, foraging behaviours ...
Marianna Chimienti, Akiko Kato, Vahid Seydi, Stefan Schoombie, Jefferson T. Hinke, Ruth Joy, Damian C. Lidgard, W. Chris Oosthuizen, Yannis P. Papastamatiou, Yan Ropert‐Coudert, Akinori Takahashi, Jean‐Baptiste Thiebot, Muriel Visani, Mickael Coustaty, Tiphaine Jeanniard‐du‐Dot   +14 more
wiley   +1 more source

Progress of AUV Intelligent Swarm Collaborative Task

水下无人系统学报, 2023
With developments in the intelligent swarm technology, the cooperation of autonomous undersea vehicle (AUV) swarms in performing underwater tasks has become an inevitable trend for the future development of such tasks. However, owing to the particularity
Qiao HU, Zhenyi ZHAO, Haobo FENG, Chuan JIANG   +3 more
doaj   +1 more source

Autonomous navigation with constrained consistency for C-Ranger [PDF]

, 2016
Autonomous underwater vehicles (AUVs) have become the most widely used tools for undertaking complex exploration tasks in marine environments. Their synthetic ability to carry out localization autonomously and build an environmental map concurrently, in ...
He, Bo, Li, Minghui, Ying, Lulu, Yuan, Guang, Zhang, Shujing   +4 more
core  

A Critical Review on the Application and Innovation in Smart Fisheries

Engineering Reports, Volume 8, Issue 1, January 2026.
Smart fisheries powered by Artificial Intelligence (AI), Internet of Things (IoT), and machine learning can spot diseases early, monitor water in real time, and identify fish automatically, helping farmers boost yields, cut losses, and protect sustainability in countries like Bangladesh.
Shahim Uddin Saba, Fatima Ibrahim, Sabrina Islam Priti, Rayhan Pervej, Alaya Parven Alo, Mahady Hasan, Md. Tarek Habib   +6 more
wiley   +1 more source

Reliability Analysis of Multi-Autonomous Underwater Vehicle Cooperative Systems Based on Fuzzy Control

Photonics
Autonomous underwater vehicles (AUVs) perform a wide range of functions, since underwater circumstances are diverse and varied and resources are plentiful.
Yu Hao, Yuan Yao, Yanbo Zhang, Fang Zuo
doaj   +1 more source

Cooperative AUV Navigation using a Single Maneuvering Surface Craft [PDF]

, 2010
In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft.
An, P.E., Bahr, A., Bahr, A., Curcio, J., Djugash, J., Djugash, J., Djugash, J., Doucet, A., Eustice, R.M., Fallon, M.F., Freitag, L., Gadre, A.S., Gadre, A.S., Georgios Papadopoulos, Heckman, D.B., Isard, M.A., John J Leonard, Larsen, M.B., Larsen, M.B., Levine, E., Maczka, D.K., Maurice F Fallon, Milne, P.H., Nerurkar, E.D., Newman, P.M., Nicholas M Patrikalakis, Paglia, J.G., Rigby, P., Slotine, J.-J., Stokey, R., Vaganay, B., Vaganay, J., Webster, S.E., Webster, S.E.   +33 more
core   +2 more sources

CCFF‐Net: Cross‐Channel Feature Fusion Network for Underwater Object Detection

IET Image Processing, Volume 20, Issue 1, January/December 2026.
Challenging underwater environmental conditions lead to severe degradation of underwater images, such as intensity attenuation and colour distortion. This issue causes incomplete feature representation of underwater objects, posing difficulties to state‐of‐the‐art detectors.
Zhe Chen, Man Zhou, Yantao Zhu, Mingwei Shen   +3 more
wiley   +1 more source

A Method for Multi-AUV Cooperative Area Search in Unknown Environment Based on Reinforcement Learning

Journal of Marine Science and Engineering
As an emerging direction of multi-agent collaborative control technology, multiple autonomous underwater vehicle (multi-AUV) cooperative area search technology has played an important role in civilian fields such as marine resource exploration and ...
Yueming Li, Mingquan Ma, Jian Cao, Guobin Luo, Depeng Wang, Weiqiang Chen   +5 more
doaj   +1 more source