Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle
Active research on crack detection technology for structures based on unmanned aerial vehicles (UAVs) has attracted considerable attention. Most of the existing research on localization of cracks using UAVs mounted the Global Positioning System (GPS)/Inertial Measurement Unit (IMU) on the UAVs to ob...
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| Format: | Article |
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MDPI AG
2022-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/17/6711 |
| _version_ | 1797492947249266688 |
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| author | Hyun-Jung Woo Dong-Min Seo Min-Seok Kim Min-San Park Won-Hwa Hong Seung-Chan Baek |
| author_facet | Hyun-Jung Woo Dong-Min Seo Min-Seok Kim Min-San Park Won-Hwa Hong Seung-Chan Baek |
| author_sort | Hyun-Jung Woo |
| collection | DOAJ |
| description | Active research on crack detection technology for structures based on unmanned aerial vehicles (UAVs) has attracted considerable attention. Most of the existing research on localization of cracks using UAVs mounted the Global Positioning System (GPS)/Inertial Measurement Unit (IMU) on the UAVs to obtain location information. When such absolute position information is used, several studies confirmed that positioning errors of the UAVs were reflected and were in the order of a few meters. To address these limitations, in this study, without using the absolute position information, localization of cracks was defined using relative position between objects in UAV-captured images to significantly reduce the error level. Through aerial photography, a total of 97 images were acquired. Using the point cloud technique, image stitching, and homography matrix algorithm, 5 cracks and 3 reference objects were defined. Importantly, the comparative analysis of estimated relative position values and ground truth values through field measurement revealed that errors in the range 24–84 mm and 8–48 mm were obtained on the x- and y-directions, respectively. Also, RMSE errors of 37.95–91.24 mm were confirmed. In the future, the proposed methodology can be utilized for supplementing and improving the conventional methods for visual inspection of infrastructures and facilities. |
| first_indexed | 2024-03-10T01:12:56Z |
| format | Article |
| id | doaj.art-22492b7dd96945c3b16a95ec7dc2be5d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T01:12:56Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-22492b7dd96945c3b16a95ec7dc2be5d2023-11-23T14:13:16ZengMDPI AGSensors1424-82202022-09-012217671110.3390/s22176711Localization of Cracks in Concrete Structures Using an Unmanned Aerial VehicleHyun-Jung Woo0Dong-Min Seo1Min-Seok Kim2Min-San Park3Won-Hwa Hong4Seung-Chan Baek5School of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, KoreaDepartment of Architecture, Kyungil University, Gyeongsan 38428, KoreaActive research on crack detection technology for structures based on unmanned aerial vehicles (UAVs) has attracted considerable attention. Most of the existing research on localization of cracks using UAVs mounted the Global Positioning System (GPS)/Inertial Measurement Unit (IMU) on the UAVs to obtain location information. When such absolute position information is used, several studies confirmed that positioning errors of the UAVs were reflected and were in the order of a few meters. To address these limitations, in this study, without using the absolute position information, localization of cracks was defined using relative position between objects in UAV-captured images to significantly reduce the error level. Through aerial photography, a total of 97 images were acquired. Using the point cloud technique, image stitching, and homography matrix algorithm, 5 cracks and 3 reference objects were defined. Importantly, the comparative analysis of estimated relative position values and ground truth values through field measurement revealed that errors in the range 24–84 mm and 8–48 mm were obtained on the x- and y-directions, respectively. Also, RMSE errors of 37.95–91.24 mm were confirmed. In the future, the proposed methodology can be utilized for supplementing and improving the conventional methods for visual inspection of infrastructures and facilities.https://www.mdpi.com/1424-8220/22/17/6711unmanned aerial vehiclescracklocalizationconcrete structure |
| spellingShingle | Hyun-Jung Woo Dong-Min Seo Min-Seok Kim Min-San Park Won-Hwa Hong Seung-Chan Baek Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle Sensors unmanned aerial vehicles crack localization concrete structure |
| title | Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle |
| title_full | Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle |
| title_fullStr | Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle |
| title_full_unstemmed | Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle |
| title_short | Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle |
| title_sort | localization of cracks in concrete structures using an unmanned aerial vehicle |
| topic | unmanned aerial vehicles crack localization concrete structure |
| url | https://www.mdpi.com/1424-8220/22/17/6711 |
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