Shenzhen QYSEA Technology Co., LTD

Shenzhen QYSEA Technology Co., LTD

Key Technology of Unmanned Underwater Vehicle

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Courtesy of Shenzhen QYSEA Technology Co., LTD

1. Overall Technology
Underwater UAV is a highly technology-intensive and systematic project, involving dozens of professional disciplines. Each discipline restricts each other. Purely pursuing a single technical index, one will lose sight of the other. To solve these contradictions, we need to strengthen coordination in addition to a strong system concept. On the premise of meeting the overall technical requirements, the determination of individual technical indicators should take into account each other. From the point of view of hydrodynamics, in order to adapt to a wide range of navigation, the shape of underwater UAV adopts a low streamlined body. As far as possible, lightweight composite materials with light weight, high buoyancy, high strength, corrosion resistance and noise reduction are used in the structure.
 
2. Simulation Technology
Underwater UAV works in complex marine environment, and it is accomplished by intelligent control. Because of the inaccessibility of the working area, it is difficult to study and test the real hardware and software systems. For this reason, in the design stage of underwater UAV, simulation technology research should be carried out, which includes two parts:
 
3. Underwater Target Detection and Recognition Technology
At present, the underwater UAV equipment for underwater target detection and recognition is limited to synthetic aperture sonar, forward-looking sonar and three-dimensional imaging sonar.
 
4. Intelligent Control Technology
This technology is the key to improve the autonomy of Underwater Unmanned Aerial Vehicle (UAV) and accomplish various tasks in complex marine environment. Therefore, it is very important to study the software system, hardware system and control technology of UAV control system. Continuously improve the system structure, strengthen the ability to predict the future, so that the system has a more forward-looking and autonomous learning ability.

 

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