徐进, 柳宁, 李德平, 林龙新, 王高. 一种基于抓取簇和碰撞体素的工业零件抓取姿态检测算法[J]. 机器人, 2022, 44(2): 153-166. DOI: 10.13973/j.cnki.robot.210044
引用本文: 徐进, 柳宁, 李德平, 林龙新, 王高. 一种基于抓取簇和碰撞体素的工业零件抓取姿态检测算法[J]. 机器人, 2022, 44(2): 153-166. DOI: 10.13973/j.cnki.robot.210044
XU Jin, LIU Ning, LI Deping, LIN Longxin, WANG Gao. A Grasping Poses Detection Algorithm for Industrial WorkpiecesBased on Grasping Cluster and Collision Voxels[J]. ROBOT, 2022, 44(2): 153-166. DOI: 10.13973/j.cnki.robot.210044
Citation: XU Jin, LIU Ning, LI Deping, LIN Longxin, WANG Gao. A Grasping Poses Detection Algorithm for Industrial WorkpiecesBased on Grasping Cluster and Collision Voxels[J]. ROBOT, 2022, 44(2): 153-166. DOI: 10.13973/j.cnki.robot.210044

一种基于抓取簇和碰撞体素的工业零件抓取姿态检测算法

A Grasping Poses Detection Algorithm for Industrial WorkpiecesBased on Grasping Cluster and Collision Voxels

  • 摘要: 针对工业上常见的散乱堆叠零件的抓取问题,提出一种基于抓取簇和碰撞体素的抓取姿态检测算法。所提出的抓取簇是定义在零件上的连续抓取姿态集合,解决了传统方法中因采用离散固定抓取点而导致可抓取点丢失、筛选效率低的问题。先对料箱和场景点云进行体素化;然后把包含料箱或点云的体素标记为碰撞体素,并把与碰撞体素相邻的体素标记为风险体素,从而建立体素化的碰撞模型;接下来,根据抓取簇的几何性质计算出候选的抓取姿态及其对应的抓取路径;最后,通过检测抓取路径所经过的体素类型来完成快速的碰撞检测,从而筛选出最优抓取姿态。基于所提算法搭建了完整的Bin-Picking系统,并对多种实际工业场景中常见的零件进行仿真实验和实际抓取实验,结果表明:该算法能够快速、准确地检测出安全的抓取姿态,实际抓取的平均成功率达92.2%,料箱平均清空率达87.2%,较传统方法有明显提升,且抓取过程均未发生碰撞,可满足实际工业应用的要求。

     

    Abstract: Aiming at the grasping problem of scattered and stacked industrial workpieces, a grasping poses detection algorithm based on grasping cluster and collision voxels is proposed.The proposed grasping cluster is a set of continuous grasping poses on the workpiece, and solves the problems of grasping points losing and screening efficiency decreasing caused by using discrete and fixed grasping points in traditional methods.Firstly, the point cloud of scene and the bin are voxelized.Then, the voxels containing bin or point cloud are marked as collision voxels, and the voxels adjacent to the collision voxels are marked as risk voxels, so as to establish a voxelized collision model.After that, according to the geometric properties of the grasping cluster, the candidate grasping poses and corresponding grasping paths are computed.Finally, the collision detection can be quickly completed by detecting the types of voxels that the grasping paths pass through, so as to select the best grasping pose.Based on the proposed algorithm, an integral Bin-Picking system is built, and simulation experiment and actual grasping experiment are performed on various common workpieces from actual industrial situations.The results show that the algorithm can detect safe grasping poses quickly and accurately.The average success rate of grasping reaches 92.2% and the average emptying rate of bins reaches 87.2%, which obtains a significant improvement compared with traditional methods, and there is no collision during the process of grasping, which can meet the requirements of practical industrial applications.

     

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