A two-time-level model for mission and flight planning of an inhomogeneous fleet of unmanned aerial vehicles

Johannes Schmidt () and Armin Fügenschuh ()
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Johannes Schmidt: Brandenburg University of Technology Cottbus-Senftenberg
Armin Fügenschuh: Brandenburg University of Technology Cottbus-Senftenberg

Computational Optimization and Applications, 2023, vol. 85, issue 1, No 10, 293-335

Abstract: Abstract We consider the mission and flight planning problem for an inhomogeneous fleet of unmanned aerial vehicles (UAVs). Therein, the mission planning problem of assigning targets to a fleet of UAVs and the flight planning problem of finding optimal flight trajectories between a given set of waypoints are combined into one model and solved simultaneously. Thus, trajectories of an inhomogeneous fleet of UAVs have to be specified such that the sum of waypoint-related scores is maximized, considering technical and environmental constraints. Several aspects of an existing basic model are expanded to achieve a more detailed solution. A two-level time grid approach is presented to smooth the computed trajectories. The three-dimensional mission area can contain convex-shaped restricted airspaces and convex subareas where wind affects the flight trajectories. Furthermore, the flight dynamics are related to the mass change, due to fuel consumption, and the operating range of every UAV is altitude-dependent. A class of benchmark instances for collision avoidance is adapted and expanded to fit our model and we prove an upper bound on its objective value. Finally, the presented features and results are tested and discussed on several test instances using GUROBI as a state-of-the-art numerical solver.

Keywords: Mixed-integer nonlinear programming; Mission planning; Inhomogeneous fleet; Time windows; Linearization methods (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10589-023-00450-x

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