Noise Aware Path Planning and Power Management of Hybrid Fuel UAVs
arxiv(2024)
摘要
Hybrid fuel Unmanned Aerial Vehicles (UAV), through their combination of
multiple energy sources, offer several advantages over the standard single fuel
source configuration, the primary one being increased range and efficiency.
Multiple power or fuel sources also allow the distinct pitfalls of each source
to be mitigated while exploiting the advantages within the mission or path
planning. We consider here a UAV equipped with a combustion engine-generator
and battery pack as energy sources. We consider the path planning and
power-management of this platform in a noise-aware manner. To solve the path
planning problem, we first present the Mixed Integer Linear Program (MILP)
formulation of the problem. We then present and analyze a label-correcting
algorithm, for which a pseudo-polynomial running time is proven. Results of
extensive numerical testing are presented which analyze the performance and
scalability of the labeling algorithm for various graph structures, problem
parameters, and search heuristics. It is shown that the algorithm can solve
instances on graphs as large as twenty thousand nodes in only a few seconds.
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