Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model
In computer vision, the detection and tracking of moving objects has become a hot topic today. The target tracking technology in this paper refers to the visual tracking of the ground moving target by the aircraft during the flight. Since both the aircraft and the target are moving, there are backgr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Ecology and Evolution |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fevo.2023.1178990/full |
| _version_ | 1797843475733938176 |
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| author | Baohua Shen Juan Jiang Daoguo Li Feng Qian |
| author_facet | Baohua Shen Juan Jiang Daoguo Li Feng Qian |
| author_sort | Baohua Shen |
| collection | DOAJ |
| description | In computer vision, the detection and tracking of moving objects has become a hot topic today. The target tracking technology in this paper refers to the visual tracking of the ground moving target by the aircraft during the flight. Since both the aircraft and the target are moving, there are background and two motion vectors composed of the target and the background in the acquired image. Therefore, this paper proposed a research on the location and tracking of environmental pollution sources under multi-UAV vision based on the target motion model. This paper first introduced the UAV target tracking technology, and analyzed the development history and types of UAVs in detail. Then, based on the increasingly serious environmental pollution, this paper proposed to use UAV sensing technology to locate the pollution source. Finally, in the experimental part, this paper tested the UAV flight platform, and carried out the actual operation and positioning of the pollution source. The final experimental results showed that within 0 ~ 360 s, the attitude angle obtained by the gradient descent method had no divergence phenomenon, which could effectively reduce the error caused by the integration; the inclination angle deviation of the two groups of experimental equipment was within ±2.5°, the roll angle deviation was within ±3°, and the deviation angle was relatively large at some moments, but the average deviation was only 0.8°. |
| first_indexed | 2024-04-09T17:05:50Z |
| format | Article |
| id | doaj.art-e30e2ee7e71644e08b201c39b2bad1b9 |
| institution | Directory Open Access Journal |
| issn | 2296-701X |
| language | English |
| last_indexed | 2024-04-09T17:05:50Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Ecology and Evolution |
| spelling | doaj.art-e30e2ee7e71644e08b201c39b2bad1b92023-04-20T16:09:31ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2023-04-011110.3389/fevo.2023.11789901178990Location and tracking of environmental pollution sources under multi-UAV vision based on target motion modelBaohua ShenJuan JiangDaoguo LiFeng QianIn computer vision, the detection and tracking of moving objects has become a hot topic today. The target tracking technology in this paper refers to the visual tracking of the ground moving target by the aircraft during the flight. Since both the aircraft and the target are moving, there are background and two motion vectors composed of the target and the background in the acquired image. Therefore, this paper proposed a research on the location and tracking of environmental pollution sources under multi-UAV vision based on the target motion model. This paper first introduced the UAV target tracking technology, and analyzed the development history and types of UAVs in detail. Then, based on the increasingly serious environmental pollution, this paper proposed to use UAV sensing technology to locate the pollution source. Finally, in the experimental part, this paper tested the UAV flight platform, and carried out the actual operation and positioning of the pollution source. The final experimental results showed that within 0 ~ 360 s, the attitude angle obtained by the gradient descent method had no divergence phenomenon, which could effectively reduce the error caused by the integration; the inclination angle deviation of the two groups of experimental equipment was within ±2.5°, the roll angle deviation was within ±3°, and the deviation angle was relatively large at some moments, but the average deviation was only 0.8°.https://www.frontiersin.org/articles/10.3389/fevo.2023.1178990/fulldrone visionpollution source locationtarget motion modeltrackinglocation and tracking |
| spellingShingle | Baohua Shen Juan Jiang Daoguo Li Feng Qian Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model Frontiers in Ecology and Evolution drone vision pollution source location target motion model tracking location and tracking |
| title | Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model |
| title_full | Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model |
| title_fullStr | Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model |
| title_full_unstemmed | Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model |
| title_short | Location and tracking of environmental pollution sources under multi-UAV vision based on target motion model |
| title_sort | location and tracking of environmental pollution sources under multi uav vision based on target motion model |
| topic | drone vision pollution source location target motion model tracking location and tracking |
| url | https://www.frontiersin.org/articles/10.3389/fevo.2023.1178990/full |
| work_keys_str_mv | AT baohuashen locationandtrackingofenvironmentalpollutionsourcesundermultiuavvisionbasedontargetmotionmodel AT juanjiang locationandtrackingofenvironmentalpollutionsourcesundermultiuavvisionbasedontargetmotionmodel AT daoguoli locationandtrackingofenvironmentalpollutionsourcesundermultiuavvisionbasedontargetmotionmodel AT fengqian locationandtrackingofenvironmentalpollutionsourcesundermultiuavvisionbasedontargetmotionmodel |