文献类型：会议论文

英文题名：A Force-feedback Assembly Method for Micro Parts Based on SRNN

作者：Zhao, Linhui[1];Zhang, Jiancheng[1]

第一作者：赵林惠

通讯作者：Zhao, LH[1]

机构：[1]Beijing Union Univ, Sch Mechatron, Beijing 100020, Peoples R China

第一机构：北京联合大学机器人学院

通讯机构：[1]corresponding author), Beijing Union Univ, Sch Mechatron, Beijing 100020, Peoples R China.|[1141739]北京联合大学机器人学院;[11417]北京联合大学;

会议论文集：International Conference on Applied Mechanics, Materials and Manufacturing (ICAMMM 2011)

会议日期：NOV 18-20, 2011

会议地点：Shenzhen, PEOPLES R CHINA

语种：英文

外文关键词：Micro Assembly; Force Feedback; Simple Recurrent Neural Network

摘要：Force-feedback information is usful for micro-assembly system to enhence its contact sensing capability. On the basis of this view, a 3D force-feedback assembly method is proposed in this paper. It uses coordinate conversion to combine ideal pose data with pose error vector for assembly control. A kind of simple recurrent neural network (SRNN), whose weights is modified by using Levenberg-Marquardt (LM) algorithm, is applied to establish the mapping relationship between pose error vector and 6-DOF contact force/toque feedback form sensor. Experiments are carried out on backlash slider and base parts assembly to verify the performance of this method. It is proved that SRNN based on LM algorithm has good convergence ability and good fitting effects. Also,pose error can be accurately estimated and assembly searching times can be greatly reduced.