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Main Authors: Scott, Drew, Manyam, Satyanarayana G., Weintraub, Isaac E., Casbeer, David W., Kumar, Manish
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.17708
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author Scott, Drew
Manyam, Satyanarayana G.
Weintraub, Isaac E.
Casbeer, David W.
Kumar, Manish
author_facet Scott, Drew
Manyam, Satyanarayana G.
Weintraub, Isaac E.
Casbeer, David W.
Kumar, Manish
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2402_17708
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Noise Aware Path Planning and Power Management of Hybrid Fuel UAVs
Scott, Drew
Manyam, Satyanarayana G.
Weintraub, Isaac E.
Casbeer, David W.
Kumar, Manish
Optimization and Control
Combinatorics
90-08
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.
title Noise Aware Path Planning and Power Management of Hybrid Fuel UAVs
topic Optimization and Control
Combinatorics
90-08
url https://arxiv.org/abs/2402.17708