| Autor: |
Hirofumi Osumi, Tomotaka Kimura, Kouji Hirata, Chinthaka Premachandra, Jun Cheng |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Drones, Vol 7, Iss 6, p 384 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2504-446X |
| DOI: |
10.3390/drones7060384 |
| Popis: |
In this paper, we consider a drone deployment problem in situations where the number of drones to be deployed is small compared to the number of users on the ground. In this problem, drones are deployed in the air to collect information, but they cannot collect information from all ground users at once due to the limitations of their communication range. Therefore, the drones need to continue to move until they collect the information for the all ground users. To efficiently realize such drone deployment, we propose two deployment methods. One is an integer linear programming (ILP)-based deployment method and the other is an adjacent deployment method. In the ILP-based deployment method, the positions of the drones at each point in time are determined by solving an ILP problem in which the objective function is the total number of users from whom data can be collected. In contrast, in the adjacent deployment method, drones are sequentially deployed in areas with probabilities determined according to the number of user nodes in adjacent areas at which other drones are already deployed. Through numerical experiments, we show that these deployment methods can be used to efficiently collect data from user nodes on the ground. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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