基于机械臂辅助的多视角三维点云拼接算法

Multi-View 3D Point Cloud Stitching Algorithm Based on Robotic Arm Assistance

针对如何快速且准确地获取模具内部完整三维点云数据的问题,提出一种机械臂与三维视觉设备结合的三维点云拼接算法。在初拼接阶段,采用手眼标定方式获取手眼矩阵,并将各幅点云转换到机器人基坐标系,完成初步拼接,得到良好的配准初始位置。在此基础上,提出改进的迭代最近点(ICP)算法,通过结合内部形体描述子(ISS)特征获得关键点,并用随机一致性算法剔除错误匹配点,在点的匹配过程中采用点到面的方式进行匹配,最终得到完整的拼接点云。实验结果表明,所提算法在与ICP算法及其他改进的ICP算法的配准性能对比中具有良好的稳健性,算法耗时及配准误差明显下降,完整的拼接点云误差为0.12 mm,具有较高的工程实践价值。

Aiming at the problem of how to quickly and accurately obtain complete 3D point cloud data within a mold,a 3D point cloud stitching algorithm combining a robotic arm and a 3D visual device is proposed.In the initial stitching process,the hand-eye calibration method is used to obtain the hand-eye matrix,and the point cloud is converted to the robot base coordinate system to complete preliminary stitching and obtain a good initial registration position.On this basis,an improved iterative closest point(ICP) algorithm is proposed,which combines intrinsic shape signature(ISS) features to obtain key points,and uses random consistency algorithm to eliminate erroneous matching points.During the point matching process,point to face matching is used to obtain a complete spliced point cloud.The experimental results show that the proposed algorithm has good robustness in comparison with the ICP algorithm and other improved ICP algorithms in terms of registration performance,and the algorithm time consumption and registration error are significantly reduced.The error of a complete mosaic point cloud is 0.12 mm,which has high engineering practical value.