摘要
为实现机器手抓握物体时不发生脱落,首先应检测其与被抓握物体接触面上的滑移信号。提出一种基于图像识别的机器手抓握滑移检测方法,采用中心区域匹配思想的归一化互相关算法(NCC)匹配由视觉传感器实时采集到的被抓握物体表面图像,得到被抓握物体在采集图像期间的滑移情况。实验结果表明:此系统可以准确检测被抓握物体是否发生滑移及滑移的方向和大小,具有高准确度、高灵敏度等优点。
To achieve the object to be grasped by robot without shedding,the first thing to do is detecting the slipping signal between the object and the robot. A method for slipping signal detection based on image recognition is presented,use normalized cross-correlation algorithm( NCC) to match surface image of object real-time collected by the visual sensor,slipping case during collecting images of grasped object robot can be obtained by comparing these two images. Experimental results indicates that this method can accurately detect the slip signal of the object which grasping by robot and the direction and size of slipping,the method possesses advantages of high accuracy,and high sensitivity etc.
作者
邢扬
史运泽
俞竹青
XING Yang SHI Yun-ze YU Zhu-qing(School of Mechanical Engineering, Changzhou University, Changzhou 213100, China)
出处
《传感器与微系统》
CSCD
2017年第4期131-133,142,共4页
Transducer and Microsystem Technologies
基金
科技部中小企业技术创新基金项目(14C26213201195)
关键词
图像识别
机器手
滑移检测
归一化互相关
image recognition
robot hand
slipping detecting
normalized cross correlation(NCC)