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基于適應度函數的無(wú)人船遺傳算法航徑規劃
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福州大學(xué) 電氣工程與自動(dòng)化學(xué)院

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U664.82

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福建省科技引導項目(2019H0007)


The Navigation Path Planning of Unmanned Surface Vehicles Genetic Algorithm Based on Fitness Function
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    摘要:

    遺傳算法通過(guò)適應度函數選取最優(yōu)的路徑,采用了無(wú)人船轉彎半徑來(lái)改進(jìn)適應度函數,實(shí)現無(wú)人船遺傳算法航徑規劃。考慮到無(wú)人船機動(dòng)性能對航跡平滑性的要求,在初始種群中利用貝塞爾曲線(xiàn)優(yōu)化方法,將原有的折線(xiàn)路徑優(yōu)化成光滑的曲線(xiàn)路徑;在適應度函數中添加曲率判斷,以無(wú)人船最小轉彎半徑為約束條件,設置曲線(xiàn)路徑的最大曲率,最后通過(guò)適應度函數篩選出符合約束條件的光滑路徑。仿真結果表明,所提出的方法能獲得符合無(wú)人船最小轉彎半徑約束的光滑路徑,相比于平滑算法,該方法的曲率更小,收斂速度更快。

    Abstract:

    Genetic algorithm selects the optimal path through fitness function, adoptsSthe turning radius of unmanned surface vehiclesSto improve the fitness function, so as to realize the navigation path planning that the genetic calculation of unmanned surface vehicles.SConsidering the requirement of trajectory smoothness for the maneuverability of unmanned surface vehicles, the original broken line path was optimized into a smooth curve path by using Bessel curve optimization method in the initialization of population. The curvature judgment was added into the fitness function, and the maximum curvature of the curve path was set with the minimum turning radius of the unmanned surface vehicles as the constraint condition. Finally, the smooth path that met the constraint condition was selected through the fitness function.Simulation results show that the proposed method can obtain a smooth path conforming to the constraint of the minimum turning radius of unmanned surface vehicles. Compared with the smooth algorithm, the curvature of the proposed method is smaller and the convergence speed is faster.

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劉長(cháng)吉,黃宴委.基于適應度函數的無(wú)人船遺傳算法航徑規劃計算機測量與控制[J].,2020,28(5):151-155.

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  • 收稿日期:2019-10-10
  • 最后修改日期:2019-10-23
  • 錄用日期:2019-10-24
  • 在線(xiàn)發(fā)布日期: 2020-05-25
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