摘要
为提高番茄采摘机器人视觉系统的定位精度,该文提出了一种基于组合匹配方法及深度校正模型的双目立体视觉测距方法。该方法在形心匹配的基础上,将形心匹配得到的视差值作为区域匹配时设定视差范围的参考值。这样可以减小区域匹配计算量及误匹配的概率。区域匹配后,利用三角测距原理得到番茄区域对应的深度图,并将区域的深度均值作为其深度维的坐标。试验发现定位误差与测量距离间具有很好的线性相关性。通过回归分析,建立了线性回归模型,并对深度测量结果进行校正。结果表明,工作距离小于650mm时,定位误差约为-7～5mm,工作距离小于1050mm时,定位误差约为±10mm,可满足番茄采摘机器人视觉系统在大多数采摘作业环境下的工作要求。
In order to enhance the localization accuracy of harvesting robots＇ vision system,a ranging method based on binocular stereo vision technology was presented,which used a combined matching method and a calibration model for depth values.After centroid-based matching,rough parallax can be acquired to set the parallax range during area-based matching.In this way,calculated amount and error matching probability can be reduced.Then the depth map of tomato region can be obtained through triangulation ranging principle after area-based matching.Depth mean value in tomato region is regarded as the distance between tomato and camera.Experimental results showed that ranging errors and distances were linear relative,so linear regression models were set up to calibrate the ranging results after regression analysis.The ranging error was about-7~5 mm when the distance was less than 650 mm.And the ranging error was about ±10 mm when the distance was less than 1 050 mm.It can meet the need of vision system of tomato harvesting robot in most harvesting environments.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2012年第5期161-167,共7页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家高技术研究发展计划("863"计划)资助项目(2006AA10Z257)
国家自然科学基金资助项目(61105024)
关键词
机器人
测量
双目视觉
模型
番茄
组合匹配
robot
measurement
binocular vision
models
tomato
combination matching
作者简介
项荣（1978-），男（汉族），浙江临安人，讲师，博士生，中国农业工程学会会员（E040000239A），主要从事机器视觉检测技术，农业机器人等方面的研究。杭州中国计量学院质量与安全工程学院，310018。Email：xr_rongge@cjlu．edu．cn
应义斌（1964-），男（汉族），浙江宁海人，教授，博士生导师，主要从事农产品无损检测技术研究。杭州浙江大学生物系统工程与食品科学学院，310058。Email：yingyb@zju．edu．cn
