Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion
The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, di...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/4/261 |
| _version_ | 1797605693703847936 |
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| author | Pengfei Tong Xuerong Yang Yajun Yang Wei Liu Peiyi Wu |
| author_facet | Pengfei Tong Xuerong Yang Yajun Yang Wei Liu Peiyi Wu |
| author_sort | Pengfei Tong |
| collection | DOAJ |
| description | The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, disaster monitoring, and sports event broadcasting, among many other disciplines. Some applications have stricter requirements for the autonomous positioning capability of UAV clusters, requiring its positioning precision to be within the cognitive range of a human or machine. Global Navigation Satellite System (GNSS) is currently the only method that can be applied directly and consistently to UAV positioning. Even with dependable GNSS, large-scale clustering of drones might fail, resulting in drone cluster bombardment. As a type of passive sensor, the visual sensor has a compact size, a low cost, a wealth of information, strong positional autonomy and reliability, and high positioning accuracy. This automated navigation technology is ideal for drone swarms. The application of vision sensors in the collaborative task of multiple UAVs can effectively avoid navigation interruption or precision deficiency caused by factors such as field-of-view obstruction or flight height limitation of a single UAV sensor and achieve large-area group positioning and navigation in complex environments. This paper examines collaborative visual positioning among multiple UAVs (UAV autonomous positioning and navigation, distributed collaborative measurement fusion under cluster dynamic topology, and group navigation based on active behavior control and distributed fusion of multi-source dynamic sensing information). Current research constraints are compared and appraised, and the most pressing issues to be addressed in the future are anticipated and researched. Through analysis and discussion, it has been concluded that the integrated employment of the aforementioned methodologies aids in enhancing the cooperative positioning and navigation capabilities of multiple UAVs during GNSS denial. |
| first_indexed | 2024-03-11T05:04:42Z |
| format | Article |
| id | doaj.art-0929ff63ea4d4655b6e8d3ca1c013eff |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T05:04:42Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-0929ff63ea4d4655b6e8d3ca1c013eff2023-11-17T18:58:14ZengMDPI AGDrones2504-446X2023-04-017426110.3390/drones7040261Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and DiscussionPengfei Tong0Xuerong Yang1Yajun Yang2Wei Liu3Peiyi Wu4School of Aeronautics and Astronautics, Sun Yat-Sen University, Shenzhen 518106, ChinaSchool of Aeronautics and Astronautics, Sun Yat-Sen University, Shenzhen 518106, ChinaSchool of Space Command, Space Engineering University, Beijing 101416, ChinaState Key Laboratory of Geo-Information Engineering, Xi’an 710054, ChinaSchool of Aeronautics and Astronautics, Sun Yat-Sen University, Shenzhen 518106, ChinaThe employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, disaster monitoring, and sports event broadcasting, among many other disciplines. Some applications have stricter requirements for the autonomous positioning capability of UAV clusters, requiring its positioning precision to be within the cognitive range of a human or machine. Global Navigation Satellite System (GNSS) is currently the only method that can be applied directly and consistently to UAV positioning. Even with dependable GNSS, large-scale clustering of drones might fail, resulting in drone cluster bombardment. As a type of passive sensor, the visual sensor has a compact size, a low cost, a wealth of information, strong positional autonomy and reliability, and high positioning accuracy. This automated navigation technology is ideal for drone swarms. The application of vision sensors in the collaborative task of multiple UAVs can effectively avoid navigation interruption or precision deficiency caused by factors such as field-of-view obstruction or flight height limitation of a single UAV sensor and achieve large-area group positioning and navigation in complex environments. This paper examines collaborative visual positioning among multiple UAVs (UAV autonomous positioning and navigation, distributed collaborative measurement fusion under cluster dynamic topology, and group navigation based on active behavior control and distributed fusion of multi-source dynamic sensing information). Current research constraints are compared and appraised, and the most pressing issues to be addressed in the future are anticipated and researched. Through analysis and discussion, it has been concluded that the integrated employment of the aforementioned methodologies aids in enhancing the cooperative positioning and navigation capabilities of multiple UAVs during GNSS denial.https://www.mdpi.com/2504-446X/7/4/261multi-UAVabsolute positioningcollaborative active navigationdynamic topologydistributed fusion |
| spellingShingle | Pengfei Tong Xuerong Yang Yajun Yang Wei Liu Peiyi Wu Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion Drones multi-UAV absolute positioning collaborative active navigation dynamic topology distributed fusion |
| title | Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion |
| title_full | Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion |
| title_fullStr | Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion |
| title_full_unstemmed | Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion |
| title_short | Multi-UAV Collaborative Absolute Vision Positioning and Navigation: A Survey and Discussion |
| title_sort | multi uav collaborative absolute vision positioning and navigation a survey and discussion |
| topic | multi-UAV absolute positioning collaborative active navigation dynamic topology distributed fusion |
| url | https://www.mdpi.com/2504-446X/7/4/261 |
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