引用本文:李优新,毛宗源,田联房.基于图像矩与神经网络的机器人四自由度视觉伺服[J].控制理论与应用,2009,26(10):1162~1166.[点击复制]
LI You-xin,MAO Zong-yuan,TIAN Lian-fang.Visual servoing of 4DOF using image moments and neural network[J].Control Theory and Technology,2009,26(10):1162~1166.[点击复制]
基于图像矩与神经网络的机器人四自由度视觉伺服
Visual servoing of 4DOF using image moments and neural network
摘要点击 2456  全文点击 1935  投稿时间:2008-11-27  修订日期:2009-06-11
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/j.issn.1000-8152.2009.10.CCTA081321
  2009,26(10):1162-1166
中文关键词  图像矩  神经网络  机器人  视觉伺服
英文关键词  image moments  neural network  robot  visual servoing
基金项目  国家自然科学基金资助项目(30570458).
作者单位E-mail
李优新* 广东工业大学信息工程学院 Liyx@163.com 
毛宗源 华南理工大学自动化科学与工程学院  
田联房 华南理工大学自动化科学与工程学院  
中文摘要
      针对传统的视觉伺服方法中图像几何特征的标记、提取与匹配过程复杂且通用性差等问题, 本文提出了一种基于图像矩的机器人四自由度(4DOF)视觉伺服方法. 首先建立了眼在手系统中图像矩与机器人位姿之间的非线性增量变换关系, 为利用图像矩进行机器人视觉伺服控制提供了理论基础, 然后在未对摄像机与手眼关系进行标定的情况下, 利用反向传播(BP)神经网络的非线性映射特性设计了基于图像矩的机器人视觉伺服控制方案, 最后用训练好的神经网络进行了视觉伺服跟踪控制. 实验结果表明基于本文算法可实现0.5 mm的位置与0.5°的姿态跟踪精度, 验证了算法的的有效性与较好的伺服性能.
英文摘要
      To avoid the complicated marking, extracting and matching of image features in the traditional visual servoing systems and to improve the universality of the algorithm, a novel visual servoing of 4-degrees of freedom(4DOF) is proposed for an eye-in-hand robot based on image moments and neural network. First, the nonlinear transform relationship between image moments and the robot pose is developed, which provides the theoretical basis for the visual servoing using image moments. Then, a back propagation(BP) neural network is designed to map the transformation from image moments variation to the robot pose displacement with 4DOF without the external and internal parameters calibration for the camera. After this, the proposed control scheme can be applied to the robotic visual servoing. The experiment results show that the tracking error is less than 0.5 mm and 0.5°respectively in position and in orientation. This confirms the validity and satisfactory servoing performance of the proposed method.