|本期目录/Table of Contents|

[1]仲训杲,徐 敏*,仲训昱,等.基于图像的非标定视觉反馈控制机器人全局定位方法[J].厦门大学学报(自然科学版),2018,57(03):413-419.[doi:10.6043/j.issn.0438-0479.201712002]
 ZHONG Xungao,XU Min*,ZHONG Xunyu,et al.Image-based Uncalibration Visual Feedback Control Method for Robot Global Positioning[J].Journal of Xiamen University(Natural Science),2018,57(03):413-419.[doi:10.6043/j.issn.0438-0479.201712002]
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基于图像的非标定视觉反馈控制机器人全局定位方法(PDF/HTML)
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《厦门大学学报(自然科学版)》[ISSN:0438-0479/CN:35-1070/N]

卷:
57卷
期数:
2018年03期
页码:
413-419
栏目:
研究论文
出版日期:
2018-05-31

文章信息/Info

Title:
Image-based Uncalibration Visual Feedback Control Method for Robot Global Positioning
文章编号:
0438-0479(2018)03-0413-07
作者:
仲训杲1徐 敏1*仲训昱2彭侠夫2
1.厦门理工学院电气工程与自动化学院,福建 厦门 361024; 2.厦门大学航空航天学院,福建 厦门 361102
Author(s):
ZHONG Xungao1XU Min1*ZHONG Xunyu2PENG Xiafu2
1.School of Electrical Engineering and Automation,Xiamen University of Technology,Xiamen 361024,China; 2.School of Aerospace Engineering,Xiamen University,Xiamen 361102,China
关键词:
机器人视觉定位 全局状态空间 视觉反馈控制 联合学习
Keywords:
robot visual positioning global state space visual feedback control unite learning
分类号:
TP 241.2
DOI:
10.6043/j.issn.0438-0479.201712002
文献标志码:
A
摘要:
针对机器人非标定全局定位问题,研究Kalman滤波(Kalman filtering,KF)算法联合反馈型Elman神经网络(Elman neural network,ENN)学习机器人图像空间与运动空间非线性映射关系,从而建立基于图像的视觉反馈控制方法.首先利用ENN学习得到机器人全局定位的次优状态,以此为系统状态向量构建伺服系统状态方程与观测方程,进而利用KF估计得到机器人图像雅可比矩阵.其次,采用KF对ENN网络权重进行在线微调,KF联合ENN满足机器人全局定位稳定收敛的要求,并对环境干扰具有一定的自适应性.最后在摄像机参数未标定条件下,进行六自由度机器人“眼在手”(eye-in-hand)定位比较试验,结果验证了提出的非标定视觉伺服控制方法的有效性.
Abstract:
To address the robotic uncalibration global positioning problem,we studied a Kalman filtering(KF)unite feedback Elman neural network(ENN)for learning nonlinear mapping between robot image-space and movement-space,then propose an image-based visual feedback control method.First,suboptimum states were obtained by ENN global learning for robot global positioning to build the system state equation and observation equation,and further use KF to estimate the image Jacobin matrix.Second,KF also fine-tuning the ENN’s weights in real time,the KF cooperative working with ENN not only meets the global stability of the robot global positioning,but also exhibits a certain adaptability to the dynamic environment.Finally,under conditions of uncalibrate the camera parameters,many positioning comparison experiments had been carried out with six degrees of freedom "eye-in-hand" robotic to verify the effectiveness of the proposed uncalibration image visual serving method.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-12-03 录用日期:2018-03-22
基金项目:国家自然科学基金(61703356); 福建省自然科学基金(2018J05114); 福建省中青年教师教育科研项目(JAT160363); 厦门理工学院高层次人才项目(YKJ15020R)
*通信作者:xumin@xmut.edu.cn
引文格式:仲训杲,徐敏,仲训昱,等.基于图像的非标定视觉反馈控制机器人全局定位方法[J].厦门大学学报(自然科学版),2018,57(3):413-419.
Citation:ZHONG X G,XU M,ZHONG X Y,et al.Image-based uncalibration visual feedback control method for robot global positioning[J].J Xiamen Univ Nat Sci,2018,57(3):413-419.(in Chinese)
更新日期/Last Update: 1900-01-01