Stereo Vision System for Vision-Based Control of Inspection-Class ROVs
The inspection-class Remotely Operated Vehicles (ROVs) are crucial in underwater inspections. Their prime function is to allow the replacing of humans during risky subaquatic operations. These vehicles gather videos from underwater scenes that are sent online to a human operator who provides control...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/24/5075 |
| _version_ | 1797500993098743808 |
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| author | Stanisław Hożyń Bogdan Żak |
| author_facet | Stanisław Hożyń Bogdan Żak |
| author_sort | Stanisław Hożyń |
| collection | DOAJ |
| description | The inspection-class Remotely Operated Vehicles (ROVs) are crucial in underwater inspections. Their prime function is to allow the replacing of humans during risky subaquatic operations. These vehicles gather videos from underwater scenes that are sent online to a human operator who provides control. Furthermore, these videos are used for analysis. This demands an RGB camera operating at a close distance to the observed objects. Thus, to obtain a detailed depiction, the vehicle should move with a constant speed and a measured distance from the bottom. As very few inspection-class ROVs possess navigation systems that facilitate these requirements, this study had the objective of designing a vision-based control method to compensate for this limitation. To this end, a stereo vision system and image-feature matching and tracking techniques were employed. As these tasks are challenging in the underwater environment, we carried out analyses aimed at finding fast and reliable image-processing techniques. The analyses, through a sequence of experiments designed to test effectiveness, were carried out in a swimming pool using a VideoRay Pro 4 vehicle. The results indicate that the method under consideration enables automatic control of the vehicle, given that the image features are present in stereo-pair images as well as in consecutive frames captured by the left camera. |
| first_indexed | 2024-03-10T03:11:52Z |
| format | Article |
| id | doaj.art-b2d81813eaea4ed7ac9a64515bbfa3b9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:11:52Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b2d81813eaea4ed7ac9a64515bbfa3b92023-11-23T10:24:27ZengMDPI AGRemote Sensing2072-42922021-12-011324507510.3390/rs13245075Stereo Vision System for Vision-Based Control of Inspection-Class ROVsStanisław Hożyń0Bogdan Żak1Faculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, PolandFaculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, PolandThe inspection-class Remotely Operated Vehicles (ROVs) are crucial in underwater inspections. Their prime function is to allow the replacing of humans during risky subaquatic operations. These vehicles gather videos from underwater scenes that are sent online to a human operator who provides control. Furthermore, these videos are used for analysis. This demands an RGB camera operating at a close distance to the observed objects. Thus, to obtain a detailed depiction, the vehicle should move with a constant speed and a measured distance from the bottom. As very few inspection-class ROVs possess navigation systems that facilitate these requirements, this study had the objective of designing a vision-based control method to compensate for this limitation. To this end, a stereo vision system and image-feature matching and tracking techniques were employed. As these tasks are challenging in the underwater environment, we carried out analyses aimed at finding fast and reliable image-processing techniques. The analyses, through a sequence of experiments designed to test effectiveness, were carried out in a swimming pool using a VideoRay Pro 4 vehicle. The results indicate that the method under consideration enables automatic control of the vehicle, given that the image features are present in stereo-pair images as well as in consecutive frames captured by the left camera.https://www.mdpi.com/2072-4292/13/24/5075stereo vision systemvision-based controlRemotely Operated Vehicle (ROV)local image feature |
| spellingShingle | Stanisław Hożyń Bogdan Żak Stereo Vision System for Vision-Based Control of Inspection-Class ROVs Remote Sensing stereo vision system vision-based control Remotely Operated Vehicle (ROV) local image feature |
| title | Stereo Vision System for Vision-Based Control of Inspection-Class ROVs |
| title_full | Stereo Vision System for Vision-Based Control of Inspection-Class ROVs |
| title_fullStr | Stereo Vision System for Vision-Based Control of Inspection-Class ROVs |
| title_full_unstemmed | Stereo Vision System for Vision-Based Control of Inspection-Class ROVs |
| title_short | Stereo Vision System for Vision-Based Control of Inspection-Class ROVs |
| title_sort | stereo vision system for vision based control of inspection class rovs |
| topic | stereo vision system vision-based control Remotely Operated Vehicle (ROV) local image feature |
| url | https://www.mdpi.com/2072-4292/13/24/5075 |
| work_keys_str_mv | AT stanisławhozyn stereovisionsystemforvisionbasedcontrolofinspectionclassrovs AT bogdanzak stereovisionsystemforvisionbasedcontrolofinspectionclassrovs |