基于3D视觉的机器人分拣实验系统研究与设计

Robot sorting experiment system based on 3D vision

针对智能制造工程专业多学科交叉融合特点,开展了基于3D视觉的工业机器人分拣实验系统研究与设计.采用Kinect相机、工业机器人、PC机、末端执行器搭建了系统硬件实验平台;采用支持向量机算法识别目标物体,提出了将中值滤波预处理和最近邻插值修复相融合的空洞毛刺修复方法;针对待识别物体是否重叠相互遮挡设计了基于霍夫变换计算物体中心点位置及基于点云配准的位姿估计定位策略;在上位机交互界面引导下完成机器人分拣系列实验.实验结果表明:该系统能够准确识别快速稳定分拣出特定形状和颜色的目标物体,实验内容涉及机器人、机器学习、图像处理、软硬件设计等多门课程知识与技术,综合性强、开放性好,为智能制造工程专业实验室建设提供了一种综合性创新型实践平台.

In view of the multi-disciplinary integration of intelligent manufacturing engineering,a robot sorting experiment system based on 3D vision are designed.The hardware experiment platform is built using Kinect camera,industrial robot,PC,and end-effector,while a Support Vector Machine(SVM)algorithm is designed to recognize target objects.Additionally,a method of cavity burr repair is proposed which combines median filter preprocessing with nearest neighbor interpolation.To check whether the target objects overlap or block each other,a strategy based on Hough transform is designed to calculate the object’s center position and another strategy based on point cloud registration to estimate the object’s pose.Then a series of robot sorting experiments are carried out under the guidance of upper computer interactive interface.The experiment results show that the system can accurately identify and stably sort the target objects of specific shape and color.The designed experiments involve knowledges and technologies related to robot,machine learning,image processing,software&hardware design,etc.In view of its strong comprehensiveness and openness,the proposed system can provide a comprehensive and innovative practice platform for intelligent manufacturing engineering laboratory.