| Autor: |
Zhiying Liu, Xiren Miao, Zhiqiang Xie, Hao Jiang, Jing Chen |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Sensors, Vol 22, Iss 19, p 7360 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1424-8220 |
| DOI: |
10.3390/s22197360 |
| Popis: |
Realizing autonomous unmanned aerial vehicle (UAV) inspection is of great significance for power line maintenance. This paper introduces a scheme of using the structure of a tower to realize visual geographical positioning of UAV for tower inspection and presents a monocular semantic simultaneous localization and mapping (SLAM) framework termed PTI-SLAM (power tower inspection SLAM) to cope with the challenge of a tower inspection scene. The proposed scheme utilizes prior knowledge of tower component geolocation and regards geographical positioning as the estimation of transformation between SLAM and the geographic coordinates. To accomplish the robust positioning and semi-dense semantic mapping with limited computing power, PTI-SLAM combines the feature-based SLAM method with a fusion-based direct method and conveys a loosely coupled architecture of a semantic task and a SLAM task. The fusion-based direct method is specially designed to overcome the fragility of the direct method against adverse conditions concerning the inspection scene. Experiment results show that PTI-SLAM inherits the robustness advantage of the feature-based method and the semi-dense mapping ability of the direct method and achieves decimeter-level real-time positioning in the airborne system. The experiment concerning geographical positioning indicates more competitive accuracy compared to the previous visual approach and artificial UAV operating, demonstrating the potential of PTI-SLAM. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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