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• W3193638351 abstract "The coverage path planning of unmanned aerial vehicles (UAVs) is a complex optimization problem in practice, especially for those involving multiple target areas. It is challenging to comprehensively plan the inter-area visiting order and the intra-area coverage paths simultaneously. Due to the battery limitation, usually the task can hardly be finished by a single UAV, and instead a fleet of UAVs are required. In this article, we first formulate an energy-aware multi-UAV multi-area coverage path planning (EM <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$^2$</tex-math></inline-formula> CPP) model, in order to characterize the practical path planning requirements of UAVs in complex conditions. Subsequently, to accomplish the optimization task, we propose a bipartite cooperative coevolution (BiCC) algorithm that coevolves an inter-area path planning and an intra-area path planning components to obtain good solutions. The basic operators in BiCC, such as the initialization and the reproduction operators, are tailored for the task of EM <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$^2$</tex-math></inline-formula> CPP. Besides, we also develop a fast heuristic algorithm for EM <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$^2$</tex-math></inline-formula> CPP, which is able to produce approximate solutions in a short time. Simulations on real-world datasets validate the good performance of the proposed methods." @default.
• W3193638351 created "2021-08-30" @default.
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• W3193638351 date "2022-02-01" @default.
• W3193638351 modified "2023-10-16" @default.
• W3193638351 title "Bipartite Cooperative Coevolution for Energy-Aware Coverage Path Planning of UAVs" @default.
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• W3193638351 doi "https://doi.org/10.1109/tai.2021.3103143" @default.
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