文献类型：期刊文献

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, L.

机构：[1] School of Mechatronics, Beijing Union University, Beijing, 100020, China

第一机构：北京联合大学机器人学院

年份：2012

卷号：120

起止页码：489-494

外文期刊名：Applied Mechanics and Materials

收录：EI(收录号：20114714534212)

语种：英文

外文关键词：Recurrent neural networks - Errors - Micromachining

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.