Unmanned underwater vehicles (ROV/AUV) are robotic systems that can float underwater, are autonomous and remotely controlled. The first unmanned underwater vehicle on record was designed by Luppis Whitehead Automobile in the form of a torpedo in 1864. The first vehicle designed in the same sense used today was designed by Dimitri Rebikoff in 1953. Today, unmanned underwater vehicles are used in a wide range of areas such as underwater search and rescue operations, ship underwater maintenance and repair operations, taking images from dangerous environments where divers cannot enter, military use, inspection of wrecks and underwater cleaning. The design stages of underwater vehicle control system are given in this study. The system consists of control cards, communication modules, sensors, lighting and power electronics elements. The basic philosophies followed for the design of the system are modularity and safety. This situation provides ease in the organization of the components in the underwater vehicle as well as the modular structure, the test and repair stages are easily carried out. To ensure modularity, the system is divided into two subcomponents as power and control units. In addition, a computer interface is used to control the underwater vehicle. With this interface, data is exchanged with underwater vehicles so that the depth, water temperature and temperature of the sealed tube containing the electronic components can be monitored. Another task of the computer interface is to transfer the camera image taken from underwater to the user. In this study, the remote control of unmanned underwater vehicles, the power system, communication infrastructure, the design of the structure that provides the transmission of the image and sensor information taken from underwater is mentioned.
Unmanned underwater vehicles (ROV/AUV) are robotic systems that can float underwater, are autonomous and remotely controlled. Nowadays, the Navy has focused on the operational use of unmanned underwater vehicles in the defense industry and in many areas, and has increased interest in this issue. Unmanned underwater vehicles. Unmanned underwater vehicles are carried out in civilian and military applications for different and varied purposes like protection of national sources, protection of environmental sources and researchs about that, miscellaneous construction activities, police of coastal and country. Also they can use civil and military applications and they helped they have helped with much of the academic and industrial research done in recent years. To sum up they are remotely controlled vehicles with observation and exploration features. This article discusses image processing and deep learning techniques in unmanned underwater vehicles. Also it presents an in-depth review of the artificial intelligence technique and aims to contribute to our country's defense industry. The options that will enable the vehicle to succeed in autonomous missions are mentioned. The Raspberry Pi 3 microprocessor was used in autonomous missions. The Raspberry Pi Camera Module, which is compatible with the Raspberry Pi 3, is preferred. Python was used as a programming language during software process. Objects in the images taken from the camera have been identified using the OpenCV library and deep learning. The TensorFlow library which deep learning library, was used for object detection and tracking. At the beginning The Faster-RCNN-Inception-V2 model was used as the Model. However, Faster-RCNN-Inception-V2 model and Raspberry Pi 3 FPS cooperation working did not show a good performance. For this reason, the SSDLite-MobileNet-V2 model, which is fast enough for most real-time object detection applications, is preferred.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.