江苏大学学报（自然科学版）2018，Vol.39Issue(1)：86-91,114,7.DOI:10.3969/j.issn.1671-7775.2018.01.014
基于自适应子模式流形学习的三维工件位姿估计方法
3D workpiece pose estimation based on adaptive sub-pattern manifold learning
摘要
Abstract
To locate three-dimensional workpiece of monocular vision timely and accurately in complex industrial environment , a pose estimation method of three-dimensional workpiece was proposed based on adaptive sub-pattern manifold learning ( SP-IVP ) . The constructing manifold method was given by nonlinear reduction of dimension framework and reconstruction of high dimension space , and the low dimensional feature sub-space was obtained to maintain the optimal continuity of nature variable .The pose estimation of workpiece was realized based on the manifold construction method .The pose estimation method of workpiece with occlusion was proposed based on SP-IVP after the segmentation rules of adaptive sub-pattern was given .Three kinds of common workpieces were tested , and the horizontal rotation and the vertical rotation were chosen as natural variables to conduct pose estimation of workpieces with or without occlusion .The results show that the average pose estimation time of the proposed method is 73 .6 ms, which can meet the requirement of real-time processing .The positioning accuracy rates of screwdriver , crankshaft and cylinder are 95 .4%, 96 .1% and 98 .4%, respectively .The recognition accuracy of the proposed method is higher than those of other methods in different occlusion cases .The sub-pattern segmentation method is performed with higher recognition rate than the method without sub -pattern segmentation .关键词
流形学习/子模式/工件定位/本质变量/位姿/邻域Key words
manifold learning/sub-pattern/workpiece localization/natural variable/pose/neighbourhood分类
信息技术与安全科学引用本文复制引用
李林,魏新华,沈宝国..基于自适应子模式流形学习的三维工件位姿估计方法[J].江苏大学学报（自然科学版）,2018,39(1):86-91,114,7.基金项目
国家自然科学基金资助项目( 51575244 ) （ 51575244 ）
农业部公益性行业专项项目( 201503130 ) （ 201503130 ）
江苏大学高级人才基金资助项目(14JDG149) （14JDG149）
