OPTION-A*-DQN algorithm cycle payoff plot.

<div><p>In response to the inefficiencies in offshore wind farm inspections caused by path redundancy and mission omissions, this study proposes a novel path planning method for Unmanned Aerial Vehicle (UAV) inspections, integrating multi-constraint optimization and intelligent schedulin...

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Библиографические подробности
Главный автор:	Meiqing Xu (8502255) (author)
Другие авторы:	Chao Deng (329151) (author), Xiangyu Hu (4326106) (author), Yuxin Lu (225932) (author), Wenyan Xue (22676549) (author), Bin Zhu (182882) (author)
Опубликовано:	2025
Предметы:	Microbiology Neuroscience Evolutionary Biology Inorganic Chemistry Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified unmanned aerial vehicle faster simulation time encompassing wind speed dynamic obstacle avoidance deep reinforcement learning balance global navigation dimensional constraint model conventional heuristic methods heuristic search constraint optimization xlink "> study proposes simulated annealing path redundancy path distance mission omissions means algorithm local optimization intelligent scheduling improved k comparative evaluations
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OPTION-A*-DQN algorithm cycle payoff plot.

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