基于改进自适应遗传算法求解移动机器人路径的优化问题

Optimization problem of mobile robot route with improved adaptive genetic algorithm

通过对遗传算法进行自适应改进,计算出能够随时适应的遗传算子,克服了传统遗传算法的早熟收敛问题.通过运用序号法设定各货位在工作环境中的位置,建立移动机器人拣选作业的数学模型,运用改进自适应遗传算法对初始路径进行改进,得出最优解,并运用Matlab遗传算法工具箱对此进行仿真.实验结果表明,此方法收敛速度快,可以获得全局最优解,其移动机器人路径规划更加快速和有效.

By means of modification of the genetic algorithm to become an adaptive one,a genetic operator was figured out to make the adaptation realized at all times,so that overcoming the premature convergence in the traditional genetic algorithm.By setting up the position of cargo place in the work environment with the serial number method,a mathematical model was established for the picking operation of the mobile robot.By using the improved adaptive genetic algorithm,the initial path was modified and the optimal solution obtained.By using Matlab genetic algorithms box,a simulation experiment was performed.Its result showed that this method exhibited a fast convergence and could be used to get a global optimal solution so that the mobile robot path planning would be quicker and efficient.