基于机器视觉的嫁接苗移栽实时定位研究  

Real-time Localization Research of Transplanting Based on Machine Vision

作　　者：谭明豪 曹其新[1] 邱强[1] 冷春涛[1] 

机构地区：[1]上海交通大学机器人研究所,上海200240

出　　处：《农业机械学报》2016年第2期59-63,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家高技术研究发展计划(863计划)项目(2012AA10A506)

摘　　要：针对自动化育苗流程中的嫁接苗移栽环节,提出了一种基于机器视觉的嫁接苗移栽实时定位系统。该系统能根据点云信息定位每次移栽嫁接苗时穴孔的位置,并且在穴盘受迫移动后重新定位穴孔的位置。具体的方法是通过RGB传感器与红外传感器获取工作区域内的点云信息,利用点云信息,首先离线标定传送带平面方程,进而根据实时的位置信息完成穴盘与背景的在线分离;接着从分离出的穴盘点云得到对应的二维掩膜,从掩膜中的单连通区域推算出每个穴孔的位置;针对穴盘移动之后的重定位,使用了基于随机采样一致算法的单应矩阵计算方法,由历史单应矩阵从初次定位的穴孔坐标计算出当前的穴孔位置。实验表明,该定位系统能有效定位穴孔的位置,满足嫁接苗移栽要求。A machine vision based real-time localization system for transplanting machine was proposed.The system can realize real-time detection of the plug tray＇s position and get the right coordinate for each planting accurately. By off-line calibration using point cloud,equation of the conveyor belt＇s plane was determined. With the equation,the plug tray was separated from the background in the point cloud. The2 D mask was got by using the point cloud of the plug tray. Then the contour of the plug tray was detected in the 2D mask,the plug tray＇s position was determined and each hole＇s coordinate was calculated in its corresponding simple connected area before planting the first graft seedling. After that,considering the movement during each time＇s planting caused by vibration,re-localization needed to be done. To do the re-localization,SURF feature points detection was done in the color image before and after last planting.Then the SURF feature points were matched,and the homography matrix was computed based on random sample consensus algorithm,which was used to calculate the coordinate of the hole. The experiment results showed that the system could achieve high precision for localization of the hole in the transplanting plug tray and it was little influenced by the lighting conditions and background color.

关 键 词：RGBD机器视觉 图像匹配 穴盘 移栽 定位 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] S223.94[自动化与计算机技术—计算机科学与技术]