基于多层感知人工神经网络的执行机构末端综合定位

非标准化执行机构的雅可比矩阵和连杆坐标系往往难以确定,导致任务空间的定位性难以分析。论文提出并证明综合型定位方法的充分必要条件,即完成多种特别定位任务的充要条件;用反向传播的多层感知人工神经网络（MLP,multilayer perceptron neural network）求解逆运动学模型,在笛卡尔空间,把执行机构D-H（denavit-hartenberg）参数作为训练集,对神经网络进行训练;定义一个函数,判断执行机构定位到目标点的性能,即可定位性。经仿真验证,神经网络求解逆运动学模型,较传统方法缩短了计算时间,计算效率提高20%,精度提高2.4%,可定位性最小值为0.96,最优运动学函...

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Bibliographic Details
Published in农业工程学报 Vol. 32; no. 1; pp. 22 - 29
Main Author 胡燕祝 李雷远
Format Journal Article
LanguageChinese
Published 北京邮电大学自动化学院,北京,100876 2016
Subjects
控制
机械化
机械臂
模型
神经网络
逆运动学
机械化
models
控制
逆运动学
模型
neural networks
manipulator
control
inverse kinematics
神经网络
mechanization
机械臂
Online AccessGet full text
ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2016.01.003

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Summary:非标准化执行机构的雅可比矩阵和连杆坐标系往往难以确定,导致任务空间的定位性难以分析。论文提出并证明综合型定位方法的充分必要条件,即完成多种特别定位任务的充要条件;用反向传播的多层感知人工神经网络（MLP,multilayer perceptron neural network）求解逆运动学模型,在笛卡尔空间,把执行机构D-H（denavit-hartenberg）参数作为训练集,对神经网络进行训练;定义一个函数,判断执行机构定位到目标点的性能,即可定位性。经仿真验证,神经网络求解逆运动学模型,较传统方法缩短了计算时间,计算效率提高20%,精度提高2.4%,可定位性最小值为0.96,最优运动学函数值4.0349×1014。
Bibliography:11-2047/S
mechanization; control; models; manipulator; neural networks; inverse kinematics
Hu Yanzhu, Li Leiyuan （College of A utomation, Bering University of Posts and Telecommunications, Bering, 100876, China）
It is difficult to establish Jacobian matrix and determine the coordinate frames of links for non-standard actuator.A new analytical method to establish the Jacobian matrix and determine the coordinate frames for joints and links are proposed in this paper. The proposed method made the positioning analysis of end-effector easier in space. At the same time, it is necessary to prove the effectiveness of the proposed method theoretically and verify the localization and configuration capabilities through simulations. First of all, forward kinematics model was set up based on a non-standard five Degree Of Freedom（5-DOF） actuator. A frame transformation is performed from base coordinate to end-effector coordinate. The relation between two adjacent joints is defined by a homogenous pose matrix. Secondly, the ne
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.01.003