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稻油輪作無人化農(nóng)場農(nóng)機作業(yè)路徑規(guī)劃算法與移動端軟件研究
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國家自然科學基金面上項目(52075211,、31771683),、湖北省重點研發(fā)計劃項目(2021BBA240)和中央高校基本科研業(yè)務費專項


Development of Agricultural Machinery Operation Path Planning Algorithms and Mobile Software for Unmanned Rice Oil Rape Rotation Farms
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    摘要:

    稻油輪作是我國長江中下游地區(qū)水稻和油菜兩種作物種植的主要模式,。為發(fā)展稻油輪作無人化農(nóng)場,進一步降低該地區(qū)水稻和油菜種植用工成本,、提高種植效益及競爭力,本文通過分析稻油輪作無人化農(nóng)場的生產(chǎn)模式、機具類型和作業(yè)路徑規(guī)劃要求,針對稻油輪作無人化農(nóng)場典型作業(yè)環(huán)節(jié)農(nóng)機具田間自動導航作業(yè)過程的路徑需求,結(jié)合Android軟件開發(fā),、JavaPython混合編程,、云服務器和數(shù)據(jù)庫等多項技術(shù),設計了基于Android應用框架的無人化農(nóng)場智能農(nóng)機具作業(yè)運維軟件,包括地塊管理、機具屬性管理,、路徑規(guī)劃及仿真模擬和路徑導出等模塊,。在已有聯(lián)合收獲機收獲作業(yè)路徑規(guī)劃算法、播種機播種作業(yè)路徑規(guī)劃算法和無人機植保及飛防作業(yè)路徑規(guī)劃算法的基礎上,重點設計了稻收油播和水田耕整地2個典型作業(yè)環(huán)節(jié)的路徑規(guī)劃算法,并通過Chaquopy插件混合編程調(diào)用前期Python編碼實現(xiàn)的田間作業(yè)路徑規(guī)劃算法,。通過基于GoogleEarth軟件選取的典型實際田塊多算例仿真測試和基于稻收油播一體機的實機田間試驗聯(lián)合調(diào)試結(jié)果表明,所設計的移動端軟件及路徑規(guī)劃算法運行穩(wěn)定可靠,軟件人機交互性好,算法能夠針對不同機具及常見四邊形地塊提供有效的自動導航自主作業(yè)路徑,單個田塊作業(yè)路徑規(guī)劃算法在小米5Pro平板計算機等4種典型Android移動終端上的運行耗時為29~1898ms,計算效率及路徑合理性均滿足實際應用中典型作業(yè)環(huán)節(jié)無人化生產(chǎn)的需要,。所提出的算法及軟件框架,為長江中下游區(qū)域稻油輪作無人化農(nóng)場的建設提供了作業(yè)路徑規(guī)劃理論及技術(shù)支撐。

    Abstract:

    Unmanned farm will be the ultimate form of rice and oil rape cultivation in the rice oil rape rotation area in the middle and lower reaches of the Yangtze River in China. By analyzing the production mode, implement type and operation path planning requirements of unmanned farming in rice and oil rape rotation, intelligent farm implement operation and maintenance software for unmanned farming was designed based on the Android application framework, including modules of plot management, implement attribute management and path planning for the path requirements of the field operation process of typical operation links of unmanned farming for rice and oil rape rotation cultivation. On the basis of the existing algorithms of the group, focusing on designing algorithms for operation path planning in two typical processes, namely integrated rice harvesting and rapeseed sowing and paddy ploughing, and the field operation path planning algorithms coded in Python beforehand was called through the mixed programming of Chaquopy plug-in. The results of simulation test and field test showed that the designed and developed Android software was stable and reliable, with good human computer interaction, and path planning algorithms were able to provide effective operation paths for different implements and common quadrilateral plots, and the operation time of the single field operation path planning algorithm ranged from 29 ms to 1 898 ms, and the computational efficiency and rationality of the paths met the needs of unmanned production of typical operation links in the real application. The computational efficiency and path reasonableness met the needs of unmanned production in typical operations, providing theoretical and technical support for the construction of unmanned farms in the middle and lower reaches of the Yangtze River for rice and oil rape rotations.

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黃小毛,王紹帥,石逸澤,黃希亞,馬永生,羅承銘.稻油輪作無人化農(nóng)場農(nóng)機作業(yè)路徑規(guī)劃算法與移動端軟件研究[J].農(nóng)業(yè)機械學報,2025,56(2):73-82. HUANG Xiaomao, WANG Shaoshuai, SHI Yize, HUANG Xiya, MA Yongsheng, LUO Chengming. Development of Agricultural Machinery Operation Path Planning Algorithms and Mobile Software for Unmanned Rice Oil Rape Rotation Farms[J]. Transactions of the Chinese Society for Agricultural Machinery,2025,56(2):73-82.

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  • 收稿日期:2024-09-28
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  • 在線發(fā)布日期: 2025-02-10
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