A NEW TECHNIQUE FOR FULLY AUTONOMOUS AND EFFICIENT 3D ROBOTICS HAND EYE CALIBRATION
A NEW TECHNIQUE FOR FULLY AUTONOMOUS AND EFFICIENT 3D ROBOTICS HAND EYE CALIBRATION
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DOI：
10.1109/70.34770
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发表时间：
1989-06-01
期刊：
影响因子：
--
通讯作者：
LENZ, RK
中科院分区：
文献类型：
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作者：
TSAI, RY;LENZ, RK
本文介绍了一种新的技术，用于计算三维位置和方向的摄像机相对于最后一个关节的机器人操作手在眼睛的配置。这是实时3D机器人眼、眼到手和手校准三重奏的一部分，三重奏使用通用的设置和校准对象、通用的坐标系、矩阵、向量、符号和操作，特别适合机器视觉社区。它比任何现有技术更容易和更快，并且在旋转方面比使用标准分辨率相机的任何现有技术精确十倍，并且在线性精度方面等于最先进的基于视觉的技术。机器人通过刚性安装在夹具上的摄像机进行一系列自动规划的运动。在每次移动结束时，总共需要90 ms来抓取图像，提取图像特征坐标，并执行相机外部校准。机器人完成所有动作后，只需几毫秒即可完成校准。一系列通用的几何性质或引理，导致推导的最终算法，这是为了简单，效率和准确性，同时提供充足的几何和代数的见解。文中介绍了新技术，分析了影响精度的关键因素，并介绍了提高精度的措施。在IBM直角坐标机器人上进行了仿真和真实的实验，并对实验结果进行了分析。
This paper describes a new technique for computing 3D position and orientation of a camera relative to the last joint of a robot manipulator in an eye-on-hand configuration. This is part of a trio for real-time 3D robotics eye, eye-to-hand, and hand calibrations, which use a common setup and calibration object, common coordinate systems, matrices, vectors, symbols, and operations throughout the trio, and is especially suited to machine vision community. It is easier and faster than any of the existing techniques, and is ten times more accurate in rotation than any existing technique using standard resolution cameras, and equal to the state-of-the-art vision based technique in terms of linear accuracy. The robot makes a series of automatically planned movements with a camera rigidly mounted at the gripper. At the end of each move, it takes a total of 90 ms to grab an image, extract image feature coordinates, and perform camera extrinsic calibration. After the robot finishes all the movements, it takes only a few milliseconds to do the calibration. A series of generic geometric properties or lemmas are presented, leading to the derivation of the final algorithms, which are aimed at simplicity, efficiency, and accuracy while giving ample geometric and algebraic insights. Besides describing the new technique, critical factors influencing the accuracy are analyzed, and procedures for improving accuracy are introduced. Test results of both simulation and real experiments on an IBM Cartesian robot are reported and analyzed.