Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging
Abstract Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including thei...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cvi2.12053 |
| _version_ | 1798041322422009856 |
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| author | Xiuchuan Xie Tao Yang Yanning Zhang Bang Liang Linfeng Liu |
| author_facet | Xiuchuan Xie Tao Yang Yanning Zhang Bang Liang Linfeng Liu |
| author_sort | Xiuchuan Xie |
| collection | DOAJ |
| description | Abstract Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including their static and dynamic perception ability. Specifically, both three‐dimensional reconstruction for a static scene and localization for moving objects are required. Simultaneous Localization And Mapping technology has made great progress in static scene structure reconstruction and UAV self‐motion estimation. However, accurate real‐time localization of moving objects is still challenging. In this article, a global averaging based localization method is proposed to locate moving objects for a small UAV platform. Inspired by global structure from motion, this idea is applied to the localization of moving objects. To solve moving object localization, the relative motion estimation and global position optimisation methods are proposed. The proposed method was tested in various scenarios with a several trajectories. The extensive experimental results demonstrate the robustness and effectiveness of the proposed method. |
| first_indexed | 2024-04-11T22:19:56Z |
| format | Article |
| id | doaj.art-2fe7c3699656425b9c2f97b1dff27d29 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-04-11T22:19:56Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-2fe7c3699656425b9c2f97b1dff27d292022-12-22T04:00:14ZengWileyIET Computer Vision1751-96321751-96402022-02-01161122510.1049/cvi2.12053Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averagingXiuchuan Xie0Tao Yang1Yanning Zhang2Bang Liang3Linfeng Liu4National Engineering Laboratory for Integrated Aero‐Space‐Ground‐Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an ChinaNational Engineering Laboratory for Integrated Aero‐Space‐Ground‐Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an ChinaNational Engineering Laboratory for Integrated Aero‐Space‐Ground‐Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an ChinaNational Engineering Laboratory for Integrated Aero‐Space‐Ground‐Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an ChinaNational Engineering Laboratory for Integrated Aero‐Space‐Ground‐Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an ChinaAbstract Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including their static and dynamic perception ability. Specifically, both three‐dimensional reconstruction for a static scene and localization for moving objects are required. Simultaneous Localization And Mapping technology has made great progress in static scene structure reconstruction and UAV self‐motion estimation. However, accurate real‐time localization of moving objects is still challenging. In this article, a global averaging based localization method is proposed to locate moving objects for a small UAV platform. Inspired by global structure from motion, this idea is applied to the localization of moving objects. To solve moving object localization, the relative motion estimation and global position optimisation methods are proposed. The proposed method was tested in various scenarios with a several trajectories. The extensive experimental results demonstrate the robustness and effectiveness of the proposed method.https://doi.org/10.1049/cvi2.12053remotely operated vehiclesobject detectionautonomous aerial vehiclesrobot visionaircraft controlSLAM (robots) |
| spellingShingle | Xiuchuan Xie Tao Yang Yanning Zhang Bang Liang Linfeng Liu Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging IET Computer Vision remotely operated vehicles object detection autonomous aerial vehicles robot vision aircraft control SLAM (robots) |
| title | Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| title_full | Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| title_fullStr | Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| title_full_unstemmed | Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| title_short | Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| title_sort | accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging |
| topic | remotely operated vehicles object detection autonomous aerial vehicles robot vision aircraft control SLAM (robots) |
| url | https://doi.org/10.1049/cvi2.12053 |
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