移动机器人的路径规划与仿真

移动机器人的路径规划与仿真
高晓巍
【期刊名称】《计算机仿真》
【年(卷),期】2013(030)007
【摘要】During the process of applying particle swarm optimization in mobile robot' s path programming,we found some problems,such as the weakening ability of whole searching,the easily occurring phenomenon of earlymature.Then this paper put forward a better algorithm based on QPSO.The advantages of the QPSO algorithm based on 8potential model are simple model,less control parameters,stronger ability of whole searching.But at the same time,there is the disadvantage of early-maturing convergence.The paper took the perspective of diversity of population to analyze how to introduce diversity function in the iteration process of the algorithm.When the diversity of population is less than dlow,we made adaptive adjustment by diversified manipulating to sustain individual difference.In this way we can avoid the algorithm falling into local optimum and then leading to the premature phenomenon.After making simulation experiment wirh MATLAB,the findings show that this algorithm can effectively solve the programming problem of the whole static pared with the QPSO algorithm,the convergence speed and searching quality have been obviously improved.%在机器人路径优化设计的研究中,由于应用环境存在障碍物,要求寻找最优无碰路径.针对于粒子群优化算法应
用于移动机器人路径规划计算中,存在全局搜索能力弱,易出现早熟现象等问题,提出了一种QPSO算法的改进算法.采用8势阱模型的QPSO算法模型简单,控制参数少,全局搜索能力强,但存在早熟收敛的缺陷,从种群的多样性角度分析,在算法的迭代过程中,引入多样性函数,在种群的多样性小于dl.时,由多样性变异操作进行自适应调整,保持了种群中个体的差异性,避免算法陷入局部最优而出现早熟现象.在MATLAB平台上进行仿真,结果表明,改进算法能够有效地解决全局静态无碰路径优化问题,收敛速度、搜索质量与QPSO算法相比明显提高.
【总页数】4页(P379-382)
【作者】高晓巍
【作者单位】齐齐哈尔大学理学院,黑龙江齐齐哈尔 161006
【正文语种】中文
【中图分类】TP242
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