摘要
分析了机器人视觉的主要标定方法 ,并在此基础上改进了传统的两步标定法 .该方法先用两步法求出转换矩阵的初值再建立优化数学模型 ,优化计算采用快速的高斯—牛顿法 .该方法不仅具有原来两步法的诸多优点 ,如自动、快速 ,而且彻底消除了第二步存在的累积误差 ,大大提高了标定精度 .大量试验表明 ,标定精度明显优于传统的两步法 .
The traditional two-stage calibration technique is improved based on the analysis of the principal calibration methods of robot vision. The technique firstly makes use of two-stage method to solve the initial value of the transition matrix,then establishes the optimization mathematical model,and Gauss-Newton method is used in the optimization computation. The proposed technique not only possesses as many virtues as the traditional two-stage method,for example,automationc,high speed,but also completely eliminates the accumulative error existing in the second stage of the traditional method and improves the calibration accuracy greatly. Many experiments indicate that the proposed technique excels the traditional two-stage method distinctly.
出处
《机器人》
EI
CSCD
北大核心
2004年第2期139-144,共6页
Robot
基金
国家自然科学基金资助项目 (6990 4 0 0 9)
关键词
机器人视觉标定
两步标定法
优化数学模型
高斯—牛顿法
robot vision calibration
two-stage calibration method
optimization mathematical model
Gauss-Newton method