Structured-Light-Based 3D Scanning System for Industrial Manipulator in Bin Picking Application

Phuc Thanh Ly, Q. Nguyen, Ngoc Duy Hung Nguyen, P. Pham, K. Hong
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引用次数: 1

Abstract

This paper developed an industrial manipulator integrated with a structured-light-based 3D scanning system using Gray code and phase-shifting patterns, implementing the bin-picking problem. The procedure of the vision-based robotic system developed in this paper is described as follows: First, the object is reconstructed in point cloud format by projecting a series of Gray code patterns followed by four-phase shift patterns. Point clouds of the object from different views are filtered and concatenated to obtain the full cloud. The full clouds, altogether with partial clouds, then are fed to PointNet neural network as a training dataset, whose estimated grasping pose can be used to pick up the objects from a bin. By using the estimated grasping pose, the robotic arm can reach the desired position and pick the object. Experimental results indicate that the developed vision-based system can reconstruct objects and grasp different-sized objects in the bin.
基于结构光的工业机械手三维扫描系统在拣仓中的应用
本文开发了一种集成了基于结构光的三维扫描系统的工业机械手,该系统采用灰度编码和相移模式,实现了垃圾箱拾取问题。本文开发的基于视觉的机器人系统的流程如下:首先,通过投影一系列灰度编码模式和四相移模式,将目标重构为点云格式;从不同的视角对物体的点云进行过滤和连接,得到完整的云。然后将全云和部分云作为训练数据集馈送给PointNet神经网络,该神经网络估计的抓取姿态可用于从垃圾桶中抓取物体。通过估计的抓取姿态,机械臂可以到达期望的位置并拾取物体。实验结果表明,所开发的基于视觉的系统可以重构物体并抓取不同大小的物体。
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