基于遗传算法的机器人路径规划的种群初始化改进

Population Initialization Improvement of Robot Path Planning Based on Genetic Algorithm

针对遗传算法应用于机器人路径规划问题时随机生成初始种群的盲目性,对初始化算法进行了改进。首先在起点和终点所在行之间的各栅格行中随机选择一个自由栅格以保证路径的无障碍性,由于这些栅格组成的路径不连续,故设计了中点连接法连接间断点,最后对路径进行简化以避免重复路径。将此算法与文献[8]的自适应遗传算法在相同环境下仿真,实验结果表明:改进种群初始化的遗传算法能有效提高解的质量,提高进化速度。

Aiming at the blindness of randomly generating initial population when genetic algorithm is used to solve robot path planning problem,the initialization algorithm is improved.Firstly,a free grid was randomly selected among the rows between the starting point and the end point to ensure the accessibility of the path.Because the paths composed of these grids were discontinuous,a midpoint connection method was designed to connect the discontinuous points.Finally,the path was simplified to avoid repeated paths.The algorithm was simulated in the same environment as the adaptive genetic algorithm in reference[8].The experimental results show that the improved genetic algorithm can effectively improve the quality of solution and the speed of evolution.