Name
Abstract | ||
|---|---|---|
In this paper, a generic scheduling framework to manage a fleet of micro unmanned aerial vehicles (UAVs) is proposed. The objective is to employ multiple UAVs in sequential and parallel ways to cover spatially and temporally distributed events in a geographical area of interest over a long period of time. The proactive scheduling framework considers several constraints and challenges including the limited battery capacities and technical specifications of the UAVs in addition to the necessity to regularly send back the UAVs to a docking station. A mixed integer linear programming (MILP) problem aiming at minimizing the total energy consumption is formulated after a series of linearization steps. Optimal UAV scheduling solutions are then obtained using off-the-shelf software. The proposed UAV scheduling framework is formulated in a generic manner and can be applied in multiple domains comprising short and/or long-term UAV missions while ensuring uninterrupted service. The obtained results can be used as convenient benchmarks for future heuristic UAV scheduling approaches. |
Year | Venue | Keywords |
|---|---|---|
2018 | 2018 IEEE 87TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING) | Energy management, scheduling, UAV |
Field | DocType | Citations |
Heuristic,Job shop scheduling,Computer science,Docking station,Scheduling (computing),Computer network,Integer programming,Software,Energy consumption,Linearization,Distributed computing | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hakim Ghazzai | 1 | 181 | 34.97 |
| Abdullah Kadri | 2 | 171 | 22.00 |
| Mahdi Ben Ghorbel | 3 | 83 | 13.11 |
| Hamid Menouar | 4 | 188 | 14.65 |