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- W4313270151 abstract "In nature, every living creature has its unique form, imitating the form, structure and function of biological control theory, can design centralized and efficient mechanical and biological performance. This paper designs a bionic gecko that moves on the wall surface. The bionic gecko adopts the attachment mode of vacuum adsorption, so that it can flexibly complete continuous movement on the wall surface and has good robustness. In view of the difference between the bionic gecko system's motion characteristics on the wall and the ground due to the influence of gravity, this paper carries out quantitative statics and hydrodynamics analysis on the bionic gecko, and the conclusion can provide effective guidance for the mechanical structure design of the bionic gecko. Bionic gecko is mainly used in wall surface defect detection. Machine vision technology combined with deep learning and image processing technology are adopted. With the above computer as the core, the bionic gecko can effectively identify wall surface defects, judge defect types and accurately locate them, and realize wall state feedback. The defect detection module and communication module collect the detection image and video results by CMOS sensor camera and send them back to the host computer. The upper computer module processed and analyzed the image data to obtain the results of cracks and defects. Meanwhile, the collected pavement image data was imported into the database for preservation, and then the feedback detection data was processed and analyzed, so as to generate the corresponding maintenance plan and carry out statistical analysis, which was convenient for professionals to repair later." @default.
- W4313270151 created "2023-01-06" @default.
- W4313270151 creator A5085787693 @default.
- W4313270151 date "2022-10-28" @default.
- W4313270151 modified "2023-10-18" @default.
- W4313270151 title "Bionic gecko based on intelligent recognition technology" @default.
- W4313270151 cites W2563631870 @default.
- W4313270151 cites W2883101151 @default.
- W4313270151 doi "https://doi.org/10.1109/icdsca56264.2022.9988130" @default.
- W4313270151 hasPublicationYear "2022" @default.
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