摘要
为了解决当前定位算法受目标背景干扰影响大,且其采用的物理接触标定技术易损伤工件表面的不足,提出了基于强定位与三点手眼标定的视觉引导算法。首先,利用高斯滤波处理Hessian矩阵,采用非极大值抑制法来确定特征点和方向,从而构造了surf特征点描述子,完成目标位置边缘和中心点的强定位,达到去除背景和环境光干扰,精确定位目标中心点与角度。然后提出三点标定法,计算缩放旋转矩阵和平移矩阵参数,完成Robot世界坐标与相机图像坐标的绑定映射。最后,编程实现算法和系统,实验测试结果显示:与当前工件材料移载系统相比,文中系统拥有更高的目标定位与标定移载成功率。
In order to solve the current localization algorithm big background interference affects calibration methods exist damage, physical contact with the workpiece material on the surface of the problem, hand-eye calibration was proposed based on strong orientation and three visual guidance systems. First, deepen the Hessian matrix, using Gaussian filter, using the maximum inhibition precisely determine the feature points and direction, in order to construct surf feature points description, finish strong positioning operator based on surf, to remove the background and the ambient light interference, the purpose of accurate positioning center of the target with Angle. And then put forward three points calibration method, calculation scale rotation matrix and translation matrix parameters, complete the Robot world coordinates and binding mapping camera image coordinates. Finally, program implementation algorithm and system, the experiment results showed that compared with the current workpiece material transfer system, this system has higher goal orientation and calibration transfer success rate.
出处
《组合机床与自动化加工技术》
北大核心
2017年第8期21-24,28,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金(61473237)
陕西省自然科学基础研究计划(2014JM2-6096)
关键词
视觉引导
强定位
三点手眼标定
缩放旋转矩阵
visual guidance
location
three point calibration of hand eye
zoom rotation matrix
