| Autor: |
Xuedi Hao, Yiming Zhang, Xueqiang Yang, Jinglin Zhang, Rusen Wen, Zhenlong Wu, Han Jia |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 13, Iss 18, p 10183 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app131810183 |
| Popis: |
Aiming at the intelligent design of underground roadway support and the precise positioning of unmanned full excavation faces, a positioning and measurement method of bolt robots based on the monocular vision principle was proposed. In this paper, a vehicle body positioning model based on image data was established. The data were obtained with a camera, and the conversion between image coordinates and world coordinates was carried out through coordinate system conversion. A monocular vision positioning system of the bolt robot was designed, and the simulation’s experimental model was established. Under the simulation’s experimental conditions, the effective positioning distance of the monocular vision positioning system was measured. An experimental platform for the bolt robot was designed, and real-time human positioning data measurement of the vehicle was carried out. The experimental error was analyzed, and the reliability of the method was proven. This method realizes the real-time positioning of underground mines through the bolt robot, improves the accuracy and efficiency of the positioning, and lays a foundation for the positioning control of the heading face and the unmanned bolt robot. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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