Dynamic Modeling of Industrial Robot Based on Support Vector Machine Regression Algorithm

摘要：

　　The industrial robot is a highly nonlinear and highly coupled device,and the calculation of the dynamic model needs to spend a lot of time,which result in difficult to achieve dynamic control.Using of intelligent algorithm to model the robot dynamics has been the field of robotics research focus.This paper proposes a method based on support vector machine regression algorithm to model the robot dynamics.The angle acceleration coefficient,and the centripetal acceleration and Coriolis acceleration coefficient,and the gravity in the robot dynamics equation are predicted based on support vector machine regression.When the support vector machine is trained,parameters in the robot dynamics equation dont rely on the position of each joint any more.Modeling process was described in detail by using a two degree of freedom robot.All the parameters are simulated.Simulation results show that the method has the characteristic of high precision,and short training time.

关键词： Industrial Robot Dynamic Modeling Support Vector Machine Algorithm

作者: Chen Hua Huang Xiao Meng Cai Gui Sheng Mao

作者单位: School of Physics and Mechatronic Engineering,Shaoguan University,Shaoguan,Guangdong,512005,China

会议类型: 国际会议

会议名称: the 2012 International Conference on Manufacturing Engineering and Automation (2012年制造工程与自动化国际会议(ICMEA2012))

会议地点: 广州

会议语种:英文

页码: 1543-1548

在线出版日期: 2012-11-16（万方平台首次上网日期，不代表论文的发表时间）