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标题：Planning Dragline Positioning Sequence with A * Search Algorithm * * The first author would like to appreciate the support of the Australian Government Research Training Program Scholarship during his research.
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作者：Haoquan Liu ; Michael Kearney ; Michael Forbes 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：12477-12483
DOI：10.1016/j.ifacol.2017.08.1924
语种：English
出版社：Elsevier
摘要：AbstractDragline excavators are among the largest earthmoving machines in surface mining, where they are used to remove the waste material that sits above a target mineral or coal reserve. The effectiveness of their operation is highly dependent on the sequence of positions at which they operate and the material movement during the excavation at each position. This paper addresses the problem of how to position a dragline in order to efficiently finish an excavation task with a specified digging and dumping strategy at each position. The dragline positioning sequence is computed among a range of candidate positions using the A* search algorithm. The algorithm is applied to two simulated dragline excavation scenarios that are defined based on actual terrain data. We show that the proposed A* algorithm is able to produce the optimal positioning sequences in a reasonable amount of computation time, allowing it to be applied in real-time decision support for the dragline operators.
关键词：KeywordsArtificial intelligenceprocess optimizationdragline operation planningdecision making