Part Pose Estimation Method Based on Fusion of BRIEF and ICP Point Cloud Registration
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.
K-D tree indexBRIEF feature matchingICP point cloud registrationpose estimation
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