Results 41 to 50 of about 1,228 (176)

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

FLSea: Underwater Visual–Inertial and Stereovision Forward‐Looking Data Sets

Journal of Field Robotics, EarlyView.
ABSTRACT Visibility underwater is challenging and degrades as the distance between the subject and the camera increases. That is why forward‐looking underwater computer vision tasks are difficult. We have collected underwater forward‐looking stereovision and visual–inertial image sets using two underwater imaging platforms, a stereo camera rig, and an ...
Yelena Randall, Ori Lifschitz, Tali Treibitz   +2 more
wiley   +1 more source

Energy-Efficient Routing for Cooperative Multi-AUV System

IFAC-PapersOnLine, 2022
Underwater robots, also known as autonomous underwater vehicles (AUVs), are amazing machines that are becoming increasingly important in a variety of disciplines, including sea environment exploration, data collection (for climate change), industry, and the military.
Kaiser, M Shamim, Hossain, Mohammad Shahadat, Mahmud, Mufti, Andersson, Karl   +3 more
openaire   +2 more sources

Multi-Auv Distributed Task Allocation Based on the Differential Evolution Quantum Bee Colony Optimization Algorithm

Polish Maritime Research, 2017
The multi-autonomous underwater vehicle (AUV) distributed task allocation model of a contract net, which introduces an equilibrium coefficient, has been established to solve the multi-AUV distributed task allocation problem.
Li Jianjun, Zhang Ru Bo
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

Formation Control With Obstacle Avoidance of Underwater Swarms Based on Relative Visual Feedback

Journal of Field Robotics, EarlyView.
ABSTRACT Underwater multi‐robot and swarm systems require advanced methodologies for controlling collective behavior. Conventional single‐robot techniques, such as tethering, sonar imaging, and acoustic localization, are not scalable or effective for swarm applications.
Andrea Infanti, Saverio Iacoponi, Saif Alameri, Mohamed El Hanbaly, Mohammed Tarnini, Cesare Stefanini, Giulia De Masi, Federico Renda   +7 more
wiley   +1 more source

Dumpsite Seabed Characterization of the San Pedro Basin, CA, From Autonomous Vehicle Observations

Journal of Field Robotics, EarlyView.
ABSTRACT A wide‐area seabed survey was conducted using autonomous underwater vehicles (AUVs) in a known dumpsite off the coast of Southern California that has been found to have widespread sediment contamination from the chemical dichlorodiphenyltrichloroethane (DDT).
Ryan A. McCarthy, Dylan Kriegman, Sophia T. Merrifield, Heidi Batchelor, Eric J. Terrill   +4 more
wiley   +1 more source

A real-time obstacle avoidance method for multi-AUV cluster based on artificial potential field

Zhongguo Jianchuan Yanjiu, 2018
[Objectives] This paper proposes a real-time obstacle avoidance method based on artificial potential field,in order to cope with the many potential obstacles in complex underwater environment which affects the movement plan for multi-autonomous ...
XU Bo, ZHANG Jiao, WANG Chao
doaj   +1 more source

Design and Motion Performance Analysis of Turbulent AUV Measuring Platform

Sensors, 2022
The use of a multi-functional autonomous underwater vehicle (AUV) as a platform for making turbulence measurements in the ocean is developed. The layout optimization of the turbulence package and platform motion performance are limitation problems in ...
Yunli Nie, Dalei Song, Zhenyu Wang, Yan Huang, Hua Yang   +4 more
doaj   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source