高技术通讯2017，Vol.27Issue(7)：625-632,8.DOI:10.3772/j.issn.1002-0470.2017.07.006
基于粒子群算法的6自由度机械臂动力学模型参数辨识
Parameter identification of a dynamic model for 6 DoF manipulators based on PSO algorithm
摘要
Abstract
A method for identification of industrial robots' dynamical parameters based on the particle swarm optimization ( PSO) algorithm is presented.The method uses the modified Newton-Euler method to constructs manipulators' lin-ear dynamical model which considers joint friction, and then, establishes an algorithm based on PSO for estimation of unknown dynamical parameters.Identification experiments are carried out for a UR industrial robot.The dynam-ic parameter estimation of the UR industrial robot is achieved by designing the excitation trajectories to excite joint motion of industrial robots and sampling relevant data.The dynamical model is validated according to the torque prediction accuracy.The experimental results show that the identification of dynamical model parameters using the proposed algorithm is accurate and effective.关键词
工业机器人/动力学模型/参数辨识/粒子群优化(PSO)算法Key words
industrial robot/dynamical model/parameter identification/particle swarm optimization ( PSO) algorithm引用本文复制引用
禹鑫燚,詹益安,洪学劲峰,欧林林..基于粒子群算法的6自由度机械臂动力学模型参数辨识[J].高技术通讯,2017,27(7):625-632,8.基金项目
863计划(2014AA041601-05),国家自然科学基金(61273116),浙江省自然科学基金(LY15F030015),浙江省公益项目(2016C31064)和宁波重点项目(2014B10017)资助. （2014AA041601-05）
