摘要
针对工业环境中板型物体(如钢板),在基于投票策略的匹配算法基础上加入了边缘点对特征,提出了一种基于边缘点对特征的三维目标识别与定位方法,并利用该算法设计实现了一个钢板识别与定位系统,已成功应用于工业机器人自动钢板打磨项目中。另外,对匹配结果使用位姿聚类以及位姿验证与优化,进一步提高了算法的准确性和鲁棒性。根据系统在工作现场的运行统计结果得出,该方法不仅定位精度在项目容忍范围之内,而且满足项目对实时性的要求。
Aiming at common planar objects in industrial environment(e. g. steel plates),on the basis of the voting-based pose estimation algorithm,this paper proposed an efficient planar object recognition and localization algorithm based on boundary point pair feature,which was successfully applied in the automatic grinding system of steel plates with industrial robot. In addition,the using of pose clustering algorithm as well as methods of pose verification and pose refinement efficiently increased the accuracy and robustness of the system. According to the statistical results of the system in industrial environment,not only the pose localization accuracy is well within the tolerances for the grasping of steel plates,but also the processing time meets the real-time requirement of the system.
作者
赵银帅
吴清潇
付双飞
张正光
Zhao Yinshuai;Wu Qingxiao;Fu Shuangfei;Zhang Zhengguang(Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China;University of Chinese Academy of Sciences,Beijing 100049,China;Key Laboratory of Opto-Electronic Information Processing,Chinese Academy of Sciences,Shenyang 110016,China;Liaoning Province Key Laboratory of Image Understanding & Computer Vision,Shenyang 110016,China)
出处
《计算机应用研究》
CSCD
北大核心
2019年第2期601-605,共5页
Application Research of Computers
基金
国家自然科学基金-深圳机器人基础研究中心项目(U1713216)
关键词
三维边缘提取
点对特征
投票策略
位姿估计
3D edge extraction
point pair feature
voting strategy
pose estimation
