基于布谷鸟算法的上料机械手轨迹优化  

Trajectory optimization of loading manipulator based on Cuckoo Search algorithm

作　　者：胡延平 王涛 王俊 崔凯 HU Yanping;WANG Tao;WANG Jun;CUI Kai

机构地区：[1]合肥工业大学机械工程学院

出　　处：《现代机械》2019年第6期10-13,共4页Modern Machinery

摘　　要：降低机械手轨迹误差对生产有重要的意义。通过相关参数和几何关系建立误差最小的目标函数,结合惩罚函数构造出适应度函数,利用布谷鸟算法进行迭代寻优,采用MATLAB对优化后的机械手四杆机构进行仿真,接着与粒子群优化算法进行比较,分析可得:采用粒子群算法优化所产生Y轴方向最大误差为-12 mm,而使用布谷鸟算法所产生的Y轴方向最大误差为-2.4mm,误差较前者降低75.3%。因此,布谷鸟算法对于该四杆机构的设计更为精确。Reducing trajectory errors of manipulator is of great importance in production.In this study,we established the objective function with the smallest error using relative parameters and geometric relations,and constructed the fitness function by combining with the penalty function,and used the Cuckoo Search algorithm for iterative optimization.The optimized four-bar manipulator was simulated by MATLAB,and compared with the particle swarm optimization algorithm.The results showed that,the maximum error on Y-axis direction generated by particle swarm optimization was-12 mm,and that by Cuckoo Search was-2.4 mm,reduced by 75.3%.Therefore,the Cuckoo Search algorithm is more accurate for the design of the four-bar manipulator.

关 键 词：布谷鸟算法 机械手 误差分析 优化 仿真 

分 类 号：TH161[机械工程—机械制造及自动化]