A ship surface intelligent cleaning robot based on YOLOv8 architecture
By combining adjustable permanent magnet magnetic attraction components, propeller negative pressure mechanism, cavitation jet and ultraviolet decontamination technology, the problems of unstable adsorption and blind spots in the coverage of ship cleaning robots during navigation are solved, achieving efficient and full-coverage cleaning effect.
CN122144083APending Publication Date: 2026-06-05SHANGHAI MARITIME UNIVERSITY
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANGHAI MARITIME UNIVERSITY
- Filing Date
- 2026-01-22
- Publication Date
- 2026-06-05
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Figure CN122144083A_ABST
Abstract
The application provides a ship surface intelligent cleaning robot based on a YOLOv8 architecture, and belongs to the technical field of ship maintenance equipment, and comprises a visual perception module, a composite adsorption module, a motion execution module, a cleaning operation module, a control hub module and a machine body bearing module for carrying each module, wherein the composite adsorption module is composed of an adjustable U-shaped permanent magnet and a propeller negative pressure adsorption structure, the cleaning operation module comprises a telescopic mechanical arm, a cavitation jet nozzle, an ultraviolet decontamination device and a protective cover arranged at the front end of the integrated bearing module. The control hub module is signal connected with each module, and controls the collaborative operation of each module. The application takes the cavitation jet technology as a cornerstone, and further combines the ultraviolet radiation technology, so that the biological adhesion layer stripping and micro-damage control are realized by optimizing the jet parameters (pressure, frequency), 99% of biological adhesion can be removed, the decontamination rate can be as high as 95%, and the decontamination rate is improved by about 35.7% compared with the prior art.
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