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基于优化遗传算法的移动机器人路径规划
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Path Planning for Mobile Robots Based on Optimized Genetic Algorithm
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    摘要:

    针对移动机器人在路径规划过程中,由于传统遗传算法中适应度函数把路径最短作为遗传到下一代主要因素,造成机器人转弯次数过多引起时间浪费问题,提出一种基于改进遗传算法的路径规划方法,通过对适应度函数添加转弯角度控制因子,把路径最短和转弯角度作为路径个体适应度函数值大小的影响因素,并对改进后的适应度函数进行了收敛性分析。最后通过MATLAB进行了仿真分析,结果表明:机器人运动轨迹更加平滑,减少了转弯次数,仿真结果说明该算法具有一定的有效性。

    Abstract:

    Aiming at the path planning of mobile robots, because the fitness function in the traditional genetic algorithm takes the shortest path as the main factor to be inherited to the next generation,too many times of robot turning lead to the problem of time waste. A path planning method based on improved genetic algorithm was proposed.By adding the control factor of turning angle to the fitness function, the shortest path and the turning angle were taken as the influencing factors of the value of the individual fitness function of the path, and the improved fitness function was analyzed for its convergence. Finally, the simulation experiments were carried out by MATLAB.The results show that the trajectory of robot is more smooth,and the number of turns has been reduced. The simulation results verify the effectiveness of the algorithm.

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王功亮,王好臣,李振雨,李家鹏.基于优化遗传算法的移动机器人路径规划[J].机床与液压,2019,47(3):37-40.
. Path Planning for Mobile Robots Based on Optimized Genetic Algorithm[J]. Machine Tool & Hydraulics,2019,47(3):37-40

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  • 在线发布日期: 2019-07-16
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