摘要
物体姿态估计在增强现实、自动驾驶和机器人操作等领域具有重要意义。在机器人抓取与辅助装配过程中实时并准确地估计目标姿态极其重要,为提高装配过程中零部件的抓取与监控的实时性与精度,研究了基于多视图特征库估计目标姿态的方法,设计融合BRIEF(Binary Robust Independent Elementary Features)特征匹配与ICP(Iterative Closest Point)点云配准的零部件姿态估计方法对零部件姿态角进行估计测量。以法兰、扳手、电钻等零件工具进行实验,实验结果表明融合BRIEF特征匹配与ICP点云配准的姿态估计方法运行耗时约200ms,而姿态估计的最大误差角度为4.5°,能有效保证零部件姿态估计方法的实时性与精度,可应用于机器人抓取作业、辅助装配监控等。
Object pose estimation is of great significance in the fields of augmented reality,autonomous driving and robot oper-ation.In the process of robot grasping and assisted assembly,real-time and accurate estimation of the target pose is extremely impor-tant.In order to improve the real-time and accuracy of the grasping and monitoring of parts during the assembly process,the method of estimating the target pose based on the multi-view feature library is studied.A part pose estimation method combining BRIEF fea-ture matching and ICP point cloud registration is designed to estimate and measure the part pose angle.Experiment with parts and tools such as flanges,wrenches,electric drills,etc.The experimental results show that the attitude estimation method fusing BRIEF feature matching and ICP point cloud registration takes about 200 milliseconds to run,and the maximum error angle of pose estima-tion is 4.5 degrees,which is effective to ensure the real-time performance and accuracy of the part pose estimation method,it can be applied to robot grasping operations,auxiliary assembly monitoring,etc.
作者
田华平
陈鹏飞
杨涛
何培垒
巩鑫
TIAN Huaping;CHEN Pengfei;YANG Tao;HE Peilei;GONG Xin(School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010;China Aviation Development Sichuan Gas Turbine Research Institute,Mianyang 621000;Key Laboratory of Sichuan Province for Robot Technology Used for Special Environment,Mianyang 621010)
出处
《计算机与数字工程》
2024年第5期1383-1387,1411,共6页
Computer & Digital Engineering
作者简介
田华平,男,硕士研究生,研究方向:机器人与机电系统、计算机视觉;陈鹏飞,男,博士,研究员,研究方向:航空发动机整机试验技术;杨涛,男,博士,教授,研究方向:机电系统建模、仿真与控制;何培垒,男,硕士,研究员,研究方向:航空发动机整机试验技术;巩鑫,男,工程师,研究方向:航空发动机整机试验技术。
