A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios
In recent years, unmanned aerial vehicles (UAVs) have become a popular and cost-effective technology in urban scenarios, encompassing applications such as material transportation, aerial photography, remote sensing, and disaster relief. However, the execution of prolonged tasks poses a heightened ch...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/7/1152 |
| _version_ | 1827286632772927488 |
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| author | Shufang Xu Ziyun Zhou Haiyun Liu Xuejie Zhang Jianni Li Hongmin Gao |
| author_facet | Shufang Xu Ziyun Zhou Haiyun Liu Xuejie Zhang Jianni Li Hongmin Gao |
| author_sort | Shufang Xu |
| collection | DOAJ |
| description | In recent years, unmanned aerial vehicles (UAVs) have become a popular and cost-effective technology in urban scenarios, encompassing applications such as material transportation, aerial photography, remote sensing, and disaster relief. However, the execution of prolonged tasks poses a heightened challenge owing to the constrained endurance of UAVs. This paper proposes a model to accurately represent urban scenarios and an unmanned system. Restricted zones, no-fly zones, and building obstructions to the detection range are introduced to make sure the model is realistic enough. We also introduced an unmanned ground vehicle (UGV) into the model to solve the endurance of the UAVs in this long-time task scenario. The UGV and UAVs constituted a heterogeneous unmanned system to collaboratively solve the path-planning problem in the model. Building upon this model, this paper designs a Three-stage Alternating Optimization Algorithm (TAOA), involving two crucial steps of prediction and rolling optimization. A three-stage scheme is introduced to rolling optimization to effectively address the complex optimization process for the unmanned system. Finally, the TAOA was experimentally validated in both synthetic scenarios and scenarios modeled based on a real-world location to demonstrate their reliability. The experiments conducted in the synthetic scenarios aimed to assess the algorithm under hypothetical conditions, while the experiments in the scenarios based on real-world locations provided a practical evaluation of the proposed methods in more complex and authentic environments. The consistent performance observed across these experiments underscores the robustness and effectiveness of the proposed approaches, supporting their potential applicability in various real-world scenarios. |
| first_indexed | 2024-04-24T10:35:32Z |
| format | Article |
| id | doaj.art-561ef65822f84d0bbbb768ec83a81fc7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-24T10:35:32Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-561ef65822f84d0bbbb768ec83a81fc72024-04-12T13:25:28ZengMDPI AGRemote Sensing2072-42922024-03-01167115210.3390/rs16071152A Path Planning Method for Collaborative Coverage Monitoring in Urban ScenariosShufang Xu0Ziyun Zhou1Haiyun Liu2Xuejie Zhang3Jianni Li4Hongmin Gao5College of Information Science and Engineering, Hohai University, Changzhou 213200, ChinaCollege of Information Science and Engineering, Hohai University, Changzhou 213200, ChinaCollege of Information Science and Engineering, Hohai University, Changzhou 213200, ChinaCollege of Computer Science and Software Engineering, Hohai University, Nanjing 211100, ChinaCollege of Information Science and Engineering, Hohai University, Changzhou 213200, ChinaCollege of Information Science and Engineering, Hohai University, Changzhou 213200, ChinaIn recent years, unmanned aerial vehicles (UAVs) have become a popular and cost-effective technology in urban scenarios, encompassing applications such as material transportation, aerial photography, remote sensing, and disaster relief. However, the execution of prolonged tasks poses a heightened challenge owing to the constrained endurance of UAVs. This paper proposes a model to accurately represent urban scenarios and an unmanned system. Restricted zones, no-fly zones, and building obstructions to the detection range are introduced to make sure the model is realistic enough. We also introduced an unmanned ground vehicle (UGV) into the model to solve the endurance of the UAVs in this long-time task scenario. The UGV and UAVs constituted a heterogeneous unmanned system to collaboratively solve the path-planning problem in the model. Building upon this model, this paper designs a Three-stage Alternating Optimization Algorithm (TAOA), involving two crucial steps of prediction and rolling optimization. A three-stage scheme is introduced to rolling optimization to effectively address the complex optimization process for the unmanned system. Finally, the TAOA was experimentally validated in both synthetic scenarios and scenarios modeled based on a real-world location to demonstrate their reliability. The experiments conducted in the synthetic scenarios aimed to assess the algorithm under hypothetical conditions, while the experiments in the scenarios based on real-world locations provided a practical evaluation of the proposed methods in more complex and authentic environments. The consistent performance observed across these experiments underscores the robustness and effectiveness of the proposed approaches, supporting their potential applicability in various real-world scenarios.https://www.mdpi.com/2072-4292/16/7/1152UAVUGVpath planningobstacle avoidanceurban scenarios |
| spellingShingle | Shufang Xu Ziyun Zhou Haiyun Liu Xuejie Zhang Jianni Li Hongmin Gao A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios Remote Sensing UAV UGV path planning obstacle avoidance urban scenarios |
| title | A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios |
| title_full | A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios |
| title_fullStr | A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios |
| title_full_unstemmed | A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios |
| title_short | A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios |
| title_sort | path planning method for collaborative coverage monitoring in urban scenarios |
| topic | UAV UGV path planning obstacle avoidance urban scenarios |
| url | https://www.mdpi.com/2072-4292/16/7/1152 |
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