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题名: 基于神经网络的机器人位姿逆解
其他题名: THE INVERSE KINEMATICS F0R THE P0SIT10N AND 0RIENTAT10N 0F A MANIPULAT0R BASED 0N NEURAL NETW0RK
作者: 张伟
作者部门: 中国科学院沈阳自动化研究所
关键词: 神经网络,机器人,运动学逆解,无导师学习
刊名: 机器人
ISSN号: 1002-0446
出版日期: 1997
卷号: 19, 期号:2, 页码:151-154, 160
收录类别: CSCD
产权排序: 1
摘要: 本文运用神经网络求解机器人运动学位姿逆解,突破了文献局限于研究位置逆解的状况,首次实现自组织神经网络求解机器人姿态逆解.通过深入分析基于Kohonen网络原理和Widrow-Hof误差修正的M.R.S自组织神经网络及机器人运动学特性,创新了自组织神经网络训练算法并建立了一类工业机器人位姿逆解的神经网络方法.对PUMA560机器人的计算机仿真结果表明:本算法在自组织能力和定位控制精度方面有较大提高
英文摘要: A methodology is presented whereby a neural network is used to learn the inverse kinematic relationship for the position and orientation of a manipulator.For the first time the arm solution for the orientation of a manipulator using a self-organizing neural net is studied in this paper.By thoroughly studding on Martinetz、Ritter and Schulten's self-organizing neural network based on Kohonen's self-organizing mapping algorithm and Widrow-Hoff type error correction rule and closely combining the characters of the inverse kinematic relationship for a robot arm, a new training model of the self-organizing neural network is proposed The computer simulation results for a PUMA 560 robot show that this method gives great improvement in self-organizing capability and precision in training process.
语种: 中文
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/15704
Appears in Collections:沈阳自动化所知识产出(2000年前)_期刊论文

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张伟.基于神经网络的机器人位姿逆解,机器人,1997,19(2):151-154, 160
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