Underwater Platform for Intelligent Robotics and its Application in Two Visual Tracking Systems

Nishida, Yuya; Sonoda, Takashi; Yasukawa, Shinsuke; Nagano, Kazunori; Minami, Mamoru; Ishii, Kazuo; Ura, Tamaki

doi:10.20965/jrm.2018.p0238

Cited by 13 publications

(3 citation statements)

References 18 publications

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“…The Tuna-Sand only weights 380 kg and is equipped with 8 propellers and a 4-Dof manipulator. With the help of the visual tracking systems, the Tuna-Sand can complete biometric identification and sampling tasks on the seabed [ 34 – 36 ], which helps to understand resource diversity for sustainable use of marine resources.…”

Section: Development Status Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

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Over time, the utilization of the Underwater Vehicle-Manipulator System (UVMS) has steadily increased in exploring and harnessing marine resources. However, the underwater environment poses big challenges for controlling, navigating, and communicating with UVMS. These challenges have not only spurred the continuous advancement of related technologies, but also made the development of the UVMS even more captivating. This article firstly provides a review of development status of the UVMS and discusses the current limitations and future directions, and then reviews in detail the dynamic and hydrodynamic modeling methods, and analyzes the principles, advantages, and disadvantages of various approaches. Then, we try to review 2 key technologies of operation control methods, including underwater positioning and navigation technologies and vehicle-manipulator coordinated control approaches. Finally, a reasonable prospect for the future development of UVMS is given.

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Section: Development Status Of the Uvmsmentioning

confidence: 99%

Underwater Robots and Key Technologies for Operation Control

Sun,

Wang,

Hui

et al. 2024

Cyborg Bionic Syst

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show abstract

“…Therefore, it is necessary to develop the robot independently. Underwater robots come in a variety of sizes, from large to small, and research and development has been carried out depending on the purpose [2], [3]. There are also underwater robots developed for education [4].…”

Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Underwater Robot for Research and Education

Fujinaga

2024

Proceedings of International Conference on Artificial Life and Robotics

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Underwater robots are utilized for underwater observation. Generally, the development of underwater robots demands a significant amount of funds, posing a high barrier for research, development, and education. The aim of this study is to reduce these barriers, facilitating broader implementation of research, development, and education in the field of underwater robotics. This paper describes the development policy and cost of a low-cost underwater robot and discusses considerations based on the results in the robotics competition.

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“…Visual object tracking (VOT), the subfield of computer vision, is a process of continuously estimating the target state through video image sequence. In recent years, VOT has become a very active research domain due to its extensive applications in many sorts of fields such as intelligent surveillance [1], automatic driving [2], and traffic flow monitoring [3], to name a few.…”

Section: Introductionmentioning

confidence: 99%

Visual Object Multimodality Tracking Based on Correlation Filters for Edge Computing

Yang

Wei

2020

Security and Communication Networks

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In recent years, visual object tracking has become a very active research field which is mainly divided into the correlation filter-based tracking and deep learning (e.g., deep convolutional neural network and Siamese neural network) based tracking. For target tracking algorithms based on deep learning, a large amount of computation is required, usually deployed on expensive graphics cards. However, for the rich monitoring devices in the Internet of Things, it is difficult to capture all the moving targets in each device in real time, so it is necessary to perform hierarchical processing and use tracking based on correlation filtering in insensitive areas to alleviate the local computing pressure. In sensitive areas, upload the video stream to a cloud computing platform with a faster computing speed to perform an algorithm based on deep features. In this paper, we mainly focus on the correlation filter-based tracking. In the correlation filter-based tracking, the discriminative scale space tracker (DSST) is one of the most popular and typical ones which is successfully applied to many application fields. However, there are still some improvements that need to be further studied for DSST. One is that the algorithms do not consider the target rotation on purpose. The other is that it is a very heavy computational load to extract the histogram of oriented gradient (HOG) features from too many patches centered at the target position in order to ensure the scale estimation accuracy. To address these two problems, we introduce the alterable patch number for target scale tracking and the space searching for target rotation tracking into the standard DSST tracking method and propose a visual object multimodality tracker based on correlation filters (MTCF) to simultaneously cope with translation, scale, and rotation in plane for the tracked target and to obtain the target information of position, scale, and attitude angle at the same time. Finally, in Visual Tracker Benchmark data set, the experiments are performed on the proposed algorithms to show their effectiveness in multimodality tracking.

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Underwater Platform for Intelligent Robotics and its Application in Two Visual Tracking Systems

Cited by 13 publications

References 18 publications

Underwater Robots and Key Technologies for Operation Control

Underwater Robots and Key Technologies for Operation Control

Development of a Low-Cost Underwater Robot for Research and Education

Visual Object Multimodality Tracking Based on Correlation Filters for Edge Computing

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