Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint
The unsatisfactory energy density of the state-of-art batteries imposes constraints on the practical application of unmanned aerial vehicles (UAVs). Establishing a UAV airport network that integrates energy supply and information exchange functionalities represents an ideal solution for enabling syn...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Energy and AI |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546824000958 |
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| author | Qi Wang Haomin Zhu Gang Pan Jianguo Wei Chen Zhang Zhu Huang Guowei Ling |
| author_facet | Qi Wang Haomin Zhu Gang Pan Jianguo Wei Chen Zhang Zhu Huang Guowei Ling |
| author_sort | Qi Wang |
| collection | DOAJ |
| description | The unsatisfactory energy density of the state-of-art batteries imposes constraints on the practical application of unmanned aerial vehicles (UAVs). Establishing a UAV airport network that integrates energy supply and information exchange functionalities represents an ideal solution for enabling synergistic UAV operations. However, devising efficient distribution protocols for these airports remains a challenge. By leveraging modeling and analysis of the energy density of existing UAV batteries, we can forecast the flight range and distances achievable by UAVs. Here, we propose a distribution protocol for UAV airport platforms aimed at enhancing distribution accuracy by the use of AI principles. Furthermore, considering the possibility of emergency UAV stop, we introduce an emergency stop system in conjunction with standard stopping procedures to optimize distribution efficiency and enhance UAV inspection safety. Moreover, existing UAV airports usually provide energy to UAVs without harnessing UAVs to facilitate interconnection and interoperability among different airports. This inefficiency leads to significant resource wastage in energy distribution. To address this, we introduce a shared energy network that allows different companies to operate according to energy distribution needs. This network not only supplies energy to UAVs but also employs UAVs for energy collection and transportation, facilitating energy trading, business collaboration, and data transmission among diverse organizations. By enabling ubiquitous energy trading, this study provides us an ideal strategy for the future construction of energy network with interconnection and interoperability, which can be extended to other applications calling for energy distribution. |
| format | Article |
| id | doaj-art-e6677026b0134993b18e92cea0958dcf |
| institution | OA Journals |
| issn | 2666-5468 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy and AI |
| spelling | doaj-art-e6677026b0134993b18e92cea0958dcf2025-08-20T01:57:59ZengElsevierEnergy and AI2666-54682024-12-011810042910.1016/j.egyai.2024.100429Distributed decision making for unmanned aerial vehicle inspection with limited energy constraintQi Wang0Haomin Zhu1Gang Pan2Jianguo Wei3Chen Zhang4Zhu Huang5Guowei Ling6Tianjin Renai College, Tianjin, 301636, ChinaNational Industry-Education Platform of Energy Storage, Tianjin University, Tianjin, 300350, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin, 300350, China; National Industry-Education Platform of Energy Storage, Tianjin University, Tianjin, 300350, China; Correspondence to: 55-A-201, College of Intelligence and Computing & National Industry-Education Platform of Energy Storage, Tianjin University, No. 135 Yaguan Road, Haihe Education Park, Tianjin, 300350, China.College of Intelligence and Computing, Tianjin University, Tianjin, 300350, ChinaSchool of Marine Science and Technology, Tianjin University, Tianjin, 300072, China; Corresponding author.College of Intelligence and Computing, Tianjin University, Tianjin, 300350, ChinaNational Industry-Education Platform of Energy Storage, Tianjin University, Tianjin, 300350, China; Correspondence to: 55-A-201, College of Intelligence and Computing & National Industry-Education Platform of Energy Storage, Tianjin University, No. 135 Yaguan Road, Haihe Education Park, Tianjin, 300350, China.The unsatisfactory energy density of the state-of-art batteries imposes constraints on the practical application of unmanned aerial vehicles (UAVs). Establishing a UAV airport network that integrates energy supply and information exchange functionalities represents an ideal solution for enabling synergistic UAV operations. However, devising efficient distribution protocols for these airports remains a challenge. By leveraging modeling and analysis of the energy density of existing UAV batteries, we can forecast the flight range and distances achievable by UAVs. Here, we propose a distribution protocol for UAV airport platforms aimed at enhancing distribution accuracy by the use of AI principles. Furthermore, considering the possibility of emergency UAV stop, we introduce an emergency stop system in conjunction with standard stopping procedures to optimize distribution efficiency and enhance UAV inspection safety. Moreover, existing UAV airports usually provide energy to UAVs without harnessing UAVs to facilitate interconnection and interoperability among different airports. This inefficiency leads to significant resource wastage in energy distribution. To address this, we introduce a shared energy network that allows different companies to operate according to energy distribution needs. This network not only supplies energy to UAVs but also employs UAVs for energy collection and transportation, facilitating energy trading, business collaboration, and data transmission among diverse organizations. By enabling ubiquitous energy trading, this study provides us an ideal strategy for the future construction of energy network with interconnection and interoperability, which can be extended to other applications calling for energy distribution.http://www.sciencedirect.com/science/article/pii/S2666546824000958UAV distribution systemHedgeEnergy constraintEnergy network |
| spellingShingle | Qi Wang Haomin Zhu Gang Pan Jianguo Wei Chen Zhang Zhu Huang Guowei Ling Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint Energy and AI UAV distribution system Hedge Energy constraint Energy network |
| title | Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| title_full | Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| title_fullStr | Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| title_full_unstemmed | Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| title_short | Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| title_sort | distributed decision making for unmanned aerial vehicle inspection with limited energy constraint |
| topic | UAV distribution system Hedge Energy constraint Energy network |
| url | http://www.sciencedirect.com/science/article/pii/S2666546824000958 |
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