基于改进北方苍鹰优化算法的工业机器人几何参数标定
Geometric parameter calibration of industrial robots based on improved Northern Goshawk Optimization algorithm
劳淞 1潘亚娟 2胡义华3
作者信息
- 1. 柳州职业技术大学机电工程学院,广西 柳州 545006
- 2. 柳州工学院机械工程学院,广西柳州 545616
- 3. 广西科技大学机械与汽车工程学院,广西柳州 545006
- 折叠
摘要
为保证工业机器人的工作性能,提高其末端定位精度,文中将北方苍鹰优化算法(NGO)应用于工业机器人几何参数标定中,并针对NGO存在的不足提出了改进北方苍鹰优化算法(INGO).INGO在NGO的基础上,在勘探阶段引入Levy飞行策略,在开发阶段引入柯西变异策略,增强了算法的寻优性能.将INGO应用于RB1200型工业机器人几何参数标定实例中,结果表明:INGO能够快速标定机器人几何参数,经标定后的绝对定位精度与标定前,以及经NGO标定的结果相比有大幅提高,体现了改进算法的优势.
Abstract
In this article,in order to ensure the working performance of industrial robots and improve their end positioning accuracy,the Northern Goshawk Optimization(NGO)algorithm is firstly applied to the geometric parameter calibration of indus-trial robots.Then,the improved Northern Goshawk Optimization algorithm(INGO)is proposed to overcome the shortcomings of NGO.Based on NGO,INGO introduces Levy Flight Strategy in the exploration phase and Cauchy Mutation Strategy in the devel-opment phase,which enhances its optimization performance.Besides,INGO is applied to the example of geometric parameter cal-ibration for the RB1200 industrial robot.The results show that INGO can quickly calibrate the robot's geometric parameters;the absolute positioning accuracy after calibration has significantly improved,compared with that before calibration and that of NGO.Therefore,it is verified that INGO has obvious advantages.
关键词
工业机器人/几何参数标定/北方苍鹰优化算法/Levy飞行策略/柯西变异策略Key words
industrial robot/geometric parameter calibration/Northern Goshawk Optimization algorithm(NGO)/Levy Flight Strategy/Cauchy Mutation Strategy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据