摘要
文中提出一种基于改进遗传算法的移动机器人路径规划方法,将复杂的二维编码问题简化为一维编码问题,优化改进标准遗传算法的选择算子和交叉算子,引入路径规划特定的遗传算子(修正算子),最后以移动机器人行走路径最短作为适应度函数进行遗传优化。此算法克服了标准遗传算法的早熟收敛、运算结果稳定性差等问题,提高遗传算法的进化效率。仿真实验结果验证了该算法在移动机器人路径规划中的可行性和有效性,以及规划结果的稳健性。
Proposes a method of moving robot path planning based on.modified genetic algorithm, which the complex two dimension coding problem is converted into the one dimension ones, which the standard selection operator and crossover operator are optimized, and which a specifically genetic operator （modifiability operator） is introduced. At the same time, the fitness function meets the requirement of the shortest period of working length. This method increases greatly the efficiency of the algorithm and overcomes the problem of premature convergence and the poor stability of simulation results of the simple genetic algorithm. Experimental results show the feasibility and effectiveness of the algorithm in path planning, and the stability of the simulation results.
出处
《计算机技术与发展》
2009年第7期20-23,共4页
Computer Technology and Development
基金
安徽省自然科学基金重点研究项目(KJ2007A052)
关键词
机器人
路径规划
遗传算法
robot
path planning
genetic algorithm
