机器人运动学参数标定的改进麻雀搜索算法  

Robot Dynamic Parameter Calibration Based on Improved Sparrow Search Algorithm

作　　者：储琴[1] 吕继东[2] CHU Qin;LÜJidong(Intelligent manufacturing School,Changzhou Engineering Vocational and Technical College,Changzhou Jiangsu 213164,China;School of Microelectronics and Control Engineering,Changzhou University,Changzhou Jiangsu 213164,China)

机构地区：[1]常州工程职业技术学院智能制造学院,江苏常州213164 [2]常州大学微电子与控制工程学院,江苏常州213164

出　　处：《机械设计与研究》2022年第3期52-55,59,共5页Machine Design And Research

基　　金：江苏省自然科学青年基金资助项目(BK20140266)。

摘　　要：机器人运动学参数标定的好坏,决定了机器人的定位精度。为减少机器人定位误差,提高定位精度,提出了一种改进麻雀搜索算法(ISSA)进行机器人运动学参数标定。ISSA算法是在麻雀搜索算法(SSA)的基础上,将Levy飞行步长策略引入到SSA中,在增强算法局部搜索能力的同时,能够大大降低陷入局部最优的风险,从而获得更好的运动学参数标定效果。为验证方法的有效性,进行了仿真实验和实测实验,结果表明,ISSA将机器人的平均距离误差由2.9464降低为了0.3752,验证了方法的有效性。Calibration of the dynamic parameters determines the positioning accuracy of the robot.In order to reduce the positioning error and improve the positioning accuracy,an improved sparrow search algorithm(ISSA)is proposed to calibrate the robot dynamic parameters.On the basis of sparrow search algorithm(SSA),ISSA introduces Levy flight step strategy into SSA which can not only enhance the local search ability of the algorithm,but also significantly reduce the risk of falling into local optimal.In order to verify the effectiveness of the proposed method,simulation experiments and field experiments are carried out.The results show that ISSA improves the average distance error of the robot from 2.9464 mm to 0.3572 mm,which verifies the effectiveness of the proposed method.

关 键 词：运动学参数 标定 麻雀搜索算法 Levy飞行 

分 类 号：TP206.3[自动化与计算机技术—检测技术与自动化装置]