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基于蟻群算法的移動機器人全局路徑規(guī)劃方法研究
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國家科技重大專項資助項目(2009ZX04014)


Research on Method of Global Path-planning for Mobile Robot Based on Ant-colony Algorithm
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    摘要:

    依據(jù)蟻群算法的特點,對移動機器人的全局路徑規(guī)劃方法進(jìn)行了研究。采用柵格法描述移動機器人的環(huán)境信息,仿真分析了蟻群算法的主要參數(shù)如蟻群數(shù)量m、啟發(fā)因子α、期望啟發(fā)因子β和信息素?fù)]發(fā)系數(shù)ρ等對規(guī)劃路徑的長度和路徑規(guī)劃效率的影響。研究結(jié)果表明,當(dāng)算法的參數(shù)匹配時,獲得的規(guī)劃路徑不僅長度短,且路徑規(guī)劃效率高。通過仿真找到了最佳匹配參數(shù)組?;诜抡娼Y(jié)果,對工作在不同環(huán)境下的移動機器人進(jìn)行了全局路徑規(guī)劃仿真實驗,研究結(jié)果驗證了蟻群算法最佳匹配參數(shù)組的準(zhǔn)確性。

    Abstract:

    The global path-planning method for MR is studied based on the characteristics of ant colony algorithm. The environment information of a plane on which mobile robot (MR) works is expressed by the grid method. The main parameters used by ant colony algorithm, such as the number of ant m, arouse factor α, expected arouse factor βand information element hangover coefficients ρ, which affect the result of path planned, including the length of the path planned and the efficiency planning path, are simulated. It is found from the simulation result that the better global path can be gotten. The length of the path planned is shorter and the efficiency of planning path is higher when the parameters m,α,βand ρ are matched better. Based on the results of above simulation, the path is planned for MR, which works on two different work-plane using ant colony algorithm with the best matching parameters obtained from the simulation. The accuracy of theoretical research is verified by the global path planned for MR working under the different work-plane. 

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史恩秀,陳敏敏,李俊,黃玉美.基于蟻群算法的移動機器人全局路徑規(guī)劃方法研究[J].農(nóng)業(yè)機械學(xué)報,2014,45(6):53-57. Shi Enxiu, Chen Minmin, Li Jun, Huang Yumei. Research on Method of Global Path-planning for Mobile Robot Based on Ant-colony Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(6):53-57.

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  • 收稿日期:2013-07-07
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  • 在線發(fā)布日期: 2014-06-10
  • 出版日期: 2014-06-10