研发了基于眼固定安装方式的机器人定位系统，提出了一种方便有效的手眼标定方法。
We developed a fixed in workspace vision positioning system of robot, and present a convenience and effective hand - eye calibration method.
该方法通过保持机器人连杆三到机器人基坐标系的旋转矩阵恒定来直接获得世界坐标，简化复杂的手眼标定和相机标定。
The method is keeping the rotation array between robot's connecting-rod 3 and robot reference coordinate constant, which can simplify the complicated hand-eye calibration and camera calibration.
针对目前机器人手眼标定的方法大多需要求解手眼标定的基本方程，提出了一种新的用于机器人手眼标定中初值估计的方法。
Considering that in most hand-eye calibration methods, the basic equation needs to be solved, a new initial estimates method for robotic hand-eye calibration was proposed.
通过该方法，可以避免随机运动序列中存在的小角度运动以及纯平移一类的退化情况对标定精度的影响，得到符合手眼标定精度的要求。
By using motion selection, the bad effect of small rotations and the degenerate motions such as pure translations will be removed and the accuracy of online hand-eye calibration be improved.
对摄像机成像模型进行了分析，论述了机器人手眼系统标定原理。
The imaging model of the camera is analyzed; the calibration principle of robot eye-in-hand system is discussed.
通过控制装有摄像机的机械手的运动，给出了一种新的机器人手眼系统标定方法。
We present a new hand-eye calibration method on the basis of controlling motion of manipulator mounted with a camera.
这一方法简化了机器人手眼系统标定过程，提高了定位精度，同时推广了手眼视觉系统的应用范围。
This method simplifies the complicated process of robot hand-eye system calibration and improves the positioning precision, meanwhile, it extends the application range of hand-eye vision system.
本文研究利用神经网络实现雅可比矩阵模型的机器人手眼协调无标定动态系统的跟踪性能。
The paper studies performance of the uncalibrated hand-eye coordination system, whose image Jacobian matrix is estimated by Neural Network way.
提出了一种用于空间物体定位的机器人手眼视觉标定新方法。
A new effective orientation method used by hand eye vision system is proposed.
提出了一种适于机器人手眼系统进行双目测距的简单的测量标定方法。
The eye-in-hand vision system is an important type of robotic vision system.
提出了一种适于机器人手眼系统进行双目测距的简单的测量标定方法。
The eye-in-hand vision system is an important type of robotic vision system.
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