Results 41 to 50 of about 22,799 (225)

Collaborative Sampling and Imaging of Phytoplankton Communities by Two Long‐Range Autonomous Underwater Vehicles Using Acoustic Tracking and Messaging

Journal of Field Robotics, EarlyView.
ABSTRACT Collaborative operation of multiple autonomous underwater vehicles (AUVs) can effectively achieve scientific goals that are hard to achieve by independently operated vehicles. Some science payloads are large, expensive, and need to be installed in the vehicle's nose cone. A vehicle can only carry one such payload.
Yanwu Zhang, Brian Kieft, Monique Messié, Quinn Shemet, Brett W. Hobson, Paul Roberts, Brent Jones, Michael Anderson, Thom Maughan, Varsha Senthil   +9 more
wiley   +1 more source

AUV-Based Plume Tracking: A Simulation Study

Journal of Control Science and Engineering, 2016
This paper presents a simulation study of an autonomous underwater vehicle (AUV) navigation system operating in a GPS-denied environment. The AUV navigation method makes use of underwater transponder positioning and requires only one transponder.
Awantha Jayasiri, Raymond G. Gosine, George K. I. Mann, Peter McGuire   +3 more
doaj   +1 more source

Enabling Under Ice Glider Operations: A Backseat Driver Approach

Journal of Field Robotics, EarlyView.
ABSTRACT Polar Oceans are key locations for forcing global ocean circulation, influencing both global climate and biogeochemical cycles. Due to restricted access to these seasonally and perennially ice‐covered regions, these areas are severely undersampled.
Yaomei Wang, Benjamin Allsup, Georgios Salavasidis, Stephen Woodward, Adeniyi Adenaya, Mike Smart, Alexis Johnson, Felipe Marques Dos Santos, Jake Ludgate, Daniel Matterson, Alvaro Lorenzo, J. Alexander Brearley, Alexander Brian Phillips   +12 more
wiley   +1 more source

A 2D Optimal Path Planning Algorithm for Autonomous Underwater Vehicle Driving in Unknown Underwater Canyons

Journal of Marine Science and Engineering, 2021
This research aims to solve the safe navigation problem of autonomous underwater vehicles (AUVs) in deep ocean, which is a complex and changeable environment with various mountains.
Yu-shan Sun, Xiao Luo, Xiangrui Ran, Guo-cheng Zhang   +3 more
semanticscholar   +1 more source

Virtual Elastic Tether: A New Approach for Multi‐Agent Navigation in Confined Aquatic Environments

Journal of Field Robotics, EarlyView.
ABSTRACT Underwater navigation is a challenging area in the field of mobile robotics due to inherent constraints in self‐localization and communication in underwater environments. Some of these challenges can be mitigated by using collaborative multi‐agent teams.
Kanzhong Yao, Xueliang Cheng, Keir Groves, Barry Lennox, Ognjen Marjanovic, Simon Watson   +5 more
wiley   +1 more source

AUV Adaptive Sampling Methods: A Review

Applied Sciences, 2019
Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours ...
Jimin Hwang, Neil Bose, Shuangshuang Fan
doaj   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source

Three-Dimensional Underwater Path Planning Based on Modified Potential Field Algorithm in Time-Varying Current

Polish Maritime Research, 2023
The article addresses the three-dimensional (3D) underwater path planning problem of an autonomous underwater vehicle (AUV) in a time-varying current.
Wang Shasha, Feng Guilin, Wang Dan, Tuo Yulong   +3 more
doaj   +1 more source

Comparing convolutional neural network and random forest for benthic habitat mapping in Apollo Marine Park

Remote Sensing in Ecology and Conservation, EarlyView.
A comparison of Convolutional Neural Network (CNN) and Random Forest (RF) model predictions of benthic habitats within Apollo Marine Park. The CNN (left) and RF (right) classification maps show the spatial distribution of three habitat types: high energy circalittoral rock with seabed‐covering sponges, low complexity circalittoral rock with non‐crowded
Henry Simmons, Dang Nguyen, Benjamin Misiuk, Daniel Ierodiaconou, Sunil Gupta, Oli Dalby, Mary Young   +6 more
wiley   +1 more source

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

Journal of Marine Science and Engineering
Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater ...
Salvador López-Barajas, Alejandro Solis, Raúl Marín-Prades, Pedro J. Sanz   +3 more
doaj   +1 more source