Results 51 to 60 of about 1,858 (201)

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

Convergence Analysis on Multi-AUV Systems With Leader-Follower Architecture

IEEE Access, 2017
In multi-autonomous underwater vehicle (multi-AUV) systems, the convergence rate is characterized by the pace of consistency of the key state information for each member. The topology with leader-follower architecture is designed as a combination of an undirected graph between followers and a digraph between leaders and followers.
Xing, Wen, Zhao, Yuxin, Karimi, Hamid Reza   +2 more
openaire   +3 more sources

Robust Stabilization of a Wheeled Mobile Robot Using Model Predictive Control Based on Neurodynamics Optimization [PDF]

, 2016
In this paper, a robust model predictive control (MPC) scheme using neural network based optimization has been developed to stabilize a physically constrained mobile robot.
Chenguang Yang
core   +1 more source

Synchronous-clock range-angle relative acoustic navigation: a unified approach to multi-AUV localization, command, control, and coordination [PDF]

, 2021
© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rypkema, N., Schmidt, H., & Fischell, E.
Fischell, Erin M., Rypkema, Nicholas R., Schmidt, Henrik   +2 more
core   +2 more sources

Biodiversity research requires more motors in air, water and on land

Methods in Ecology and Evolution, EarlyView.
Abstract Human activities have accelerated species extinctions, driving rapid biodiversity decline. Simultaneously, advancements in Artificial Intelligence (AI) and autonomous systems offer transformative potential for biodiversity research. Uncrewed vehicles—drones (aerial systems) and other robots (ground and underwater platforms)—equipped with high ...
Man Qi, Matthew Gadd, Daniele De Martini, Katrina J. Davis, Biao Xiong, Alice Rosen, Sruthi M. Krishna Moorthy, Nick Hawes, Roberto Salguero‐Gómez   +8 more
wiley   +1 more source

Sub-parent AUV with multi-load release capacity: principle, mechanism design and performance testing

Zhongguo Jianchuan Yanjiu
Objective This paper proposes the concept of a sub-parent AUV to address the specific requirements of load capacity, response speed and multi-body coordination in scenarios such as underwater search and rescue, wartime defense and dense attacks.
Haochen LI, Wenchao QIAO, Hang ZHANG, Shengzeng ZHOU, Xinliang TIAN, Binrong WEN   +5 more
doaj   +1 more source

Stabilization of planar collective motion: All-to-all communication [PDF]

, 2007
This paper proposes a design methodology to stabilize isolated relative equilibria in a model of all-to-all coupled identical particles moving in the plane at unit speed.
Leonard, Naomi Ehrich, Paley, Derek, Sepulchre, Rodolphe   +2 more
core   +1 more source

Evaluating the possible role of bottom currents and internal waves in shaping seafloor morphology in a mesophotic reef

Sedimentology, EarlyView.
ABSTRACT Mesophotic reefs are located in low light conditions which, depending on the region, are usually found in water depths greater than ~30 m. They are less affected by ocean warming than reefs found in shallower water depths and thus might become increasingly important for the sustainability of marine biodiversity.
Or M. Bialik, Henriette Wilckens, Omri Gadol, Aaron Micallef, Christian Betzler, Ole Johannes R. Sørensen, Hagai Nativ, Yizhaq Makovsky   +7 more
wiley   +1 more source

Multi-AUV Cooperative Search for Moving Targets Based on Multi-Agent Reinforcement Learning

Journal of Marine Science and Engineering
This paper proposes a convolutional multi-agent deep deterministic policy gradient method with prioritized experience replay (PER-CMADDPG) for the problem of multi-AUV cooperative search for moving targets. A comprehensive mathematical model of the multi-
Le Li, Ruiqi An, Zhaozhi Guo, Jian Gao
doaj   +1 more source

An AUV Target-Tracking Method Combining Imitation Learning and Deep Reinforcement Learning

Journal of Marine Science and Engineering, 2022
This study aims to solve the problem of sparse reward and local convergence when using a reinforcement learning algorithm as the controller of an AUV.
Yubing Mao, Farong Gao, Qizhong Zhang, Zhangyi Yang   +3 more
doaj   +1 more source