| Autor: |
Baizhong CHEN, Chonglei WANG, Chunyu GUO |
| Jazyk: |
čínština |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
水下无人系统学报, Vol 31, Iss 6, Pp 911-917 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2096-3920 |
| DOI: |
10.11993/j.issn.2096-3920.2022-0099 |
| Popis: |
The bionic unmanned undersea vehicles(UUVs) replace human labor and realize underwater operation by imitating the movement principle of marine organisms. Compared with the traditional UUV, the bionic UUV has the bionics advantages of high stability, high flexibility, low noise, and strong environmental passability, which provides an excellent operating platform for close-range underwater image shooting and underwater target recognition technology. This paper focused on bionic UUVs with flexible wave propulsion by pectoral fin and conducted a comprehensive study on the preprocessing technology of underwater images and the optimization of the Resnet deep learning network, so as to improve the detection of small underwater targets on the sea floor. A series of underwater environment perception systems were developed to align with the motion characteristics of the UUV, which were then verified by the test. The results show that the proposed underwater visual detection approach achieves a classification accuracy of 89.6%, which is the highest compared with other classification networks. This approach can be used for underwater target detection on the sea floor by bionic UUVs with pectoral fin propulsion. The conclusion of the study highlights the advantages and problems of underwater detection and recognition systems of bionic UUVs and their prospects. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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